ISO/IEC DTR 23188.2
(Main)Information technology — Cloud computing — Edge computing landscape
Information technology — Cloud computing — Edge computing landscape
This document examines the concept of edge computing, its relationship to cloud computing and IoT, and the technologies that are key to the implementation of edge computing. This document explores the following topics with respect to edge computing: — concept of edge computing systems; — architectural foundation of edge computing; — edge computing terminology; — software classifications in edge computing, e.g. firmware, services, applications; — supporting technologies, e.g. containers, serverless computing, microservices; — networking for edge systems, including virtual networks; — data, e.g. data flow, data storage, data processing; — management, of software, of data and of networks, resources, quality of service; — virtual placement of software and data, and metadata; — security and privacy; — real time; — mobile edge computing, mobile devices.
Technologies de l'information — Informatique en nuage — Environnement de l'edge computing
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FINAL DRAFT
Technical
Report
ISO/IEC DTR 23188
ISO/IEC JTC 1/SC 38
Information technology — Cloud
Secretariat: ANSI
computing — Edge computing
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2025-05-13
Voting terminates on:
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ISO/IEC DTR 23188:2025(en) © ISO/IEC 2025
FINAL DRAFT
ISO/IEC DTR 23188:2025(en)
Technical
Report
ISO/IEC DTR 23188
ISO/IEC JTC 1/SC 38
Information technology — Cloud
Secretariat: ANSI
computing — Edge computing
Voting begins on:
landscape
Voting terminates on:
RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT,
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© ISO/IEC 2025
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© ISO/IEC 2025 – All rights reserved
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ISO/IEC DTR 23188:2025(en)
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Edge computing .2
3.2 IoT terms .2
3.3 Real time .3
4 Symbols and abbreviated terms. 4
5 Overview of edge computing . . 5
5.1 General .5
5.2 Concepts of edge computing .5
5.3 Architectural foundations of edge computing .7
5.4 Relationship of edge computing to cloud computing .8
5.5 Relationship of edge computing to IoT .11
6 Networking and edge computing .12
6.1 General . 12
6.1.1 Overview . 12
6.1.2 Proximity networks. 13
6.1.3 Access networks . 13
6.1.4 Services networks . 13
6.1.5 User networks . 13
6.2 Virtual networks.14
7 Hardware considerations for edge computing .15
7.1 General . 15
7.2 Hardware capabilities . 15
8 Software technologies for edge computing .16
8.1 General .16
8.2 Software classifications .16
8.2.1 Firmware . .16
8.2.2 Platform software .17
8.2.3 Services .17
8.2.4 Application .17
8.3 Significant software technologies .17
8.3.1 General .17
8.3.2 Virtual machines .18
8.3.3 Containers .18
8.3.4 Serverless computing .19
8.3.5 Microservices .19
9 Deployment models and service capabilities types and service categories for edge
computing . . 19
9.1 General .19
9.2 Deployment models .19
9.3 Service model capabilities types . 20
9.4 Service categories . 20
10 Data in edge computing .20
10.1 General . 20
10.2 Data flow .21
10.3 Data storage . 22
10.4 Data processing. 23
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ISO/IEC DTR 23188:2025(en)
11 Management of edge computing.24
11.1 Management and orchestration fundamentals .24
11.2 Management plane, control plane and data plane . 25
11.3 Cloud-based management and control of edge tier nodes and device tier devices .27
11.3.1 General .27
11.3.2 Control of services from a device .27
11.3.3 Management of devices and edge nodes from a cloud service . 28
11.4 Orchestration and maintenance . 28
11.5 Management of data, rights and resources . 28
11.6 Security and privacy management . 29
12 Virtual placement .29
13 Security and privacy in edge computing .30
13.1 General . 30
13.2 Applying foundational security principles . 30
13.3 Secure nodes and devices .31
13.4 Connectivity and network security .32
13.5 Organization of security elements . 33
13.5.1 General . 33
13.5.2 Network security . 33
13.5.3 Data security . 34
13.5.4 Application security . 34
13.5.5 Node security . 34
13.5.6 Security OSS . 35
13.6 Privacy and personally identifiable information in edge computing . 35
14 Real time in edge computing .36
14.1 Overview . 36
14.2 Factors influencing real time system design .37
14.3 Design approaches for real time edge computing . 39
15 Edge computing and mobile devices .39
Bibliography . 41
© ISO/IEC 2025 – All rights reserved
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ISO/IEC DTR 23188:2025(en)
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical activity.
ISO and IEC technical committees collaborate in fields of mutual interest. Other international organizations,
governmental and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types
of document should be noted. This document was drafted in accordance with the editorial rules of the ISO/
IEC Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the
use of (a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any
claimed patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had not
received notice of (a) patent(s) which may be required to implement this document. However, implementers
are cautioned that this may not represent the latest information, which may be obtained from the patent
database available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held
responsible for identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/iso/foreword.html.
In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 38, Cloud computing and distributed platforms.
This second edition cancels and replaces the first edition (ISO/IEC 23188:2020), which has been technically
revised.
The main changes are as follows:
— this document has been aligned with the ISO/IEC 22123 series;
— reference to ISO/IEC 17788 and ISO/IEC 17789 have been changed to the ISO/IEC 22123 series;
— verbal forms have been updated in line with the ISO/IEC Directives Part 2.
Any feedback or questions on this document should be directed to the user’s national standards
body. A complete listing of these bodies can be found at www.iso.org/members.html and
www.iec.ch/national-committees.
© ISO/IEC 2025 – All rights reserved
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ISO/IEC DTR 23188:2025(en)
Introduction
Edge computing is increasingly used in systems that deal with aspects of the physical world. Edge computing
involves the placement of processing and storage near or at the places where those systems interact with
the physical world, which is where the "edge" exists. One of the trends in this space is the development of
increasingly capable Internet of Things (IoT) devices (sensors and actuators), which generate more data or
new types of data. There is significant benefit from moving the processing and storing of this data close to
the place where the data is generated.
Cloud computing is commonly used in systems that are based on edge computing approaches. This can
include the connection of both devices and edge computing nodes to centralized cloud services. However, it
is the case that the locations in which cloud computing is performed are increasingly distributed in nature.
The cloud services are being implemented in locations that are nearer to the edge in order to support use
cases that demand reduced latency or avoiding the need to transmit large volumes of data over networks
with limited bandwidth.
This document aims to describe edge computing and the significant elements which contribute to the
successful implementation of edge computing systems, with an emphasis on the use of cloud computing and
cloud computing technologies in the context of edge computing, including the virtualization of compute,
storage and networking resources.
[15]
It is useful to read this document in conjunction with ISO/IEC TR 30164, which takes a view of edge
computing from the point of view of IoT systems and the IoT devices which interact with the physical world.
© ISO/IEC 2025 – All rights reserved
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FINAL DRAFT Technical Report ISO/IEC DTR 23188:2025(en)
Information technology — Cloud computing — Edge
computing landscape
1 Scope
This document examines the concept of edge computing, its relationship to cloud computing and IoT, and the
technologies that are key to the implementation of edge computing. This document explores the following
topics with respect to edge computing:
— concept of edge computing systems;
— architectural foundation of edge computing;
— edge computing terminology;
— software classifications in edge computing, e.g. firmware, services, applications;
— supporting technologies, e.g. containers, serverless computing, microservices;
— networking for edge computing systems, including virtual networks;
— data, e.g. data flow, data storage, data processing;
— management, of software, of data and of networks, resources, quality of service;
— virtual placement of software and data, and metadata;
— security and privacy;
— real time;
— mobile edge computing, mobile devices.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 22123-1, Information technology — Cloud computing — Part 1: Vocabulary
ISO/IEC 23167, Information technology — Cloud computing — Common technologies and techniques
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 22123-1, ISO/IEC TS 23167
and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
3.1 Edge computing
3.1.1
distributed computing
model of computing in which a set of nodes (3.1.5) coordinates its activities by means of digital messages
passed between the nodes
3.1.2
edge
boundary between pertinent digital and physical entities (3.2.8), delineated by networked sensors (3.2.9)
and actuators (3.2.1)
Note 1 to entry: Pertinent digital entities means that the digital entities which need to be considered can vary
depending on the system under consideration and the context in which those entities are used. See 5.2 for more detail.
3.1.3
edge computing
distributed computing (3.1.1) in which processing and storage takes place at or near the edge (3.1.2), where
the nearness is defined by the system's requirements
3.1.4
lightweight node
node (3.1.5) with limited processing, storage and networking capacities
3.1.5
node
networked machine with processing and storage capabilities
3.1.6
edge computing system
system providing functionalities of edge computing (3.1.3)
3.1.7
endpoint
combination of a binding and a network address
[SOURCE: ISO/TR 24097-3:2019, 3.4]
3.2 IoT terms
3.2.1
actuator
IoT device (3.2.4) that changes one or more properties of a physical entity (3.2.8) in response to a valid input
[SOURCE: ISO/IEC 20924:2024, 3.2.2]
3.2.2
Internet of Things
IoT
infrastructure of interconnected entities, people, systems and information resources together with services
which processes and reacts to information from the physical world and virtual world
[SOURCE: ISO/IEC 20924:2024, 3.2.8]
3.2.3
Internet Protocol
IP
protocol specified in RFC 791 (IP version 4) or in RFC 2460 (IP version 6)
[SOURCE: ISO/IEC TR 21890:2001, 3.4]
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
3.2.4
IoT device
entity of an IoT system (3.2.6) that interacts and communicates with the physical world through sensing or
actuating
Note 1 to entry: An IoT device (3.2.4) can be a sensor (3.2.9) or an actuator (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.11]
3.2.5
IoT gateway
entity of an IoT system (3.2.6) that connects one or more proximity networks and the IoT devices (3.2.4) on
those networks to each other and to one or more access networks
[SOURCE: ISO/IEC 20924:2024, 3.2.14]
3.2.6
IoT system
system providing functionalities of Internet of Things (3.2.2)
Note 1 to entry: IoT system is inclusive of IoT devices (3.2.4), IoT gateways (3.2.5), sensors (3.2.9), and actuators (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.15]
3.2.7
operational technology
OT
hardware and software that detects or causes a change through the direct monitoring and/or control of
physical devices and systems, processes and events in the organization
3.2.8
physical entity
entity that has material existence in the physical world
[SOURCE: ISO/IEC 20924:2024, 3.1.25]
3.2.9
sensor
IoT device (3.2.4) that measures one or more properties of one or more physical entities (3.2.8) and outputs
digital data that can be transmitted over a network
[SOURCE: ISO/IEC 20924:2024, 3.2.20]
3.3 Real time
3.3.1
real time
processing of data by a computer in connection with another process outside the computer according to
time requirements imposed by the outside process
[SOURCE: ISO/IEC 2382:2015, 2122900, modified — words 'pertaining to' removed to improve
substitutability of definition; Notes 1 to 3 to entry have been removed.]
3.3.2
real time system
system in which processing meets real time (3.3.1) requirements
3.3.3
hard real time
real time system (3.3.2) whose operation is incorrect if results are not produced according to specified
timing requirements
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
3.3.4
soft real time
real time system (3.3.2) whose operation is degraded if results are not produced according to specified
timing requirements
4 Symbols and abbreviated terms
AC Alternating current
BYOD Bring Your Own Device
CDN Content Distribution Network
CSC Cloud service customer
CSP Cloud service provider
CSU Cloud service user
DDoS Distributed Denial of Service
DevSecOps Development, Security, and Operations
EPG Electronic Programme Guide
EPROM Erasable Programmable Read Only Memory
FPGA Field Programmable Gate Array
Gb Gigabyte
GPS Global Positioning System
GPU Graphics Processing Unit
IETF Internet Engineering Task Force
IoT Internet of Things
IP Internet Protocol
IPTV Internet Protocol television
LAN Local Area Network
MDM Mobile Device Management
OS Operating system
PC Personal Computer
PII Personally Identifiable Information
RAM Random-access Memory
RFC Request for Comments
ROM Read Only Memory
TPM Trusted Platform Module
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
VM Virtual Machine
VoIP Voice over Internet Protocol
VPN Virtual Private Network
WiFi Wireless Fidelity
5 Overview of edge computing
5.1 General
Over time, the forms of computing have varied between centralized and distributed, depending on the
nature and capabilities of the computing devices and of the networks used to connect them.
Mainframe computers represent a form of centralised computing, where the main computer systems
are placed in a data centre, containing processing and storage units. Originally, almost the whole of the
computing system was situated within the data centre. Gradually, time-sharing terminals were located in
remote locations to provide user access to the mainframe systems. Terminals were typically little more than
a display with a keyboard for input and the associated network connection had limited bandwidth, perhaps
involving a dial-up modem.
The personal computer (PC) represents a distributed form of computing. The PC has significant processing
and storage capabilities and can be used very effectively in a standalone mode. However, PCs are more
typically used in a networked mode. Initially, the networks were used for simple communications such as
(text based) email, but as the network bandwidth increased over time, increasingly sophisticated activities
took place, with file transfer and eventually peer-to-peer capabilities being used.
The availability of higher bandwidth networking encouraged the development of the client-server
architecture, with the PC used for the client, connected to a centralized server which performs the main
processing and storage. Client can include quite substantial software elements performing significant
processing activities. Data might also be stored locally for faster access, although the main database(s) are
held centrally.
The advent of the internet and the World Wide Web (WWW) represents the appearance of another form
of computing. In this form of computing, web servers serve up web pages and related material which are
accessed through client web browsers. Devices running web browsers can be relatively low in compute
power, while the web servers for some of the more popular and high demand web sites can involve massive
compute power spread over many machines in a large data centre.
Cloud computing is a computing paradigm that provides various types of computing resources on demand
in a highly scalable manner through cloud computing services. In practice, it relies on a highly centralized
architecture, with computing resources concentrated in large data centres. However, cloud computing also
incorporates certain features of distributed computing. It is common for cloud service providers to operate
multiple physically separated data centres, and cloud service users (CSUs) often use applications and data
to be distributed across these centres using cloud computing service– for resilience, to reduce latency and
for disaster recovery purposes. In addition, the favoured design paradigm for cloud native applications is
to distribute multiple instances of each application component across different machines within the cloud
computing system. This design paradigm and the technologies that support it are of significance to edge
computing.
5.2 Concepts of edge computing
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities,
i.e. between the digital system and the physical world, delineated by networked sensors and actuators. The
concept of edge computing is shown in Figure 1.
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
Figure 1 — Concept of edge computing
Pertinent digital entities mean that the digital entities which need to be considered can vary depending on
the system under consideration and the context in which those entities are used.
An example of varying pertinence are the servers within a cloud computing data centre. When CSCs use cloud
services deployed on such servers to build IoT systems, it is difficult to say that the location of IoT sensors is
always at the edge. However, from the perspective of the CSPs having to manage the cloud computing data
centre, it is highly likely that the servers are instrumented with a variety of sensors capable of reporting
various physical properties of the servers, for example their temperature. Those sensors are at the edge.
Nearness for edge computing is usually based on minimising the latency for communication between the IoT
devices that are at the edge and the place(s) where data processing and storage occurs. Nearness can mean
placing the edge computing nodes physically close to the IoT devices. In the most extreme cases, nearness
means combining the sensors and actuators and edge computing into a single node, as might happen with
a smart phone. In other cases, the edge computing nodes are separated from the IoT devices but are placed
physically close to the IoT devices and have a proximity network connecting them designed to minimise
latency. Nearness can also be influenced by the nature of the networks and the volume of data flowing to
and from the IoT devices – where large volumes of data and high data rates are involved, edge nodes are
placed so as to reduce the latency of handling this data to the minimum necessary to meet the requirements
of the use case.
Digital systems can observe and affect the physical world. Sensors and actuators are at the edge between
the digital systems and the physical world. Edge computing systems generally combine these IoT devices
with distributed computing resources to provide the capabilities of the system. In edge computing systems,
actions often need to occur within specific timeframes, i.e. edge computing systems can also be real time
systems, and latency considerations affect system design and the choice of the placement of data processing
and storage to achieve timing requirements. Edge computing helps to meet those timing requirements.
Edge computing is characterized by networked systems in which significant data processing and storage
takes place on nodes near the edge, rather than in some centralized location. Edge computing can be
contrasted with centralized computing where the centralized nodes are remote from the edge. However, it is
important to note that edge computing is complementary to centralized forms of computing and that in any
given system, edge computing is often used in conjunction with centralized computing.
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
There are multiple reasons for the rise in the use of edge computing. One reason is the arrival of new devices
combining significant processing power and storage with low power usage. Smart phones have been one
of the driving factors in this area, with billions of such devices in daily use. The Internet of Things (IoT) is
another reason, with small, low power, low cost IoT devices enabling the creation of IT systems which can
sense and act on real world entities.
5.3 Architectural foundations of edge computing
Edge computing involves nodes that are highly heterogeneous, and which are commonly arranged in tiers
of compute and storage capabilities. A simplified view of the organization of edge computing nodes and the
networks connecting them in edge computing is shown in Figure 2.
Figure 2 — Organization of nodes in edge computing
The tiers shown in Figure 2 are essentially a conceptual model (containing physical elements) and are
illustrative rather than definitive – in reality the number of tiers and the type of node in each tier and the
networks connecting them are variable, depending on the nature of the system involved. What is important
to understand is that there are multiple tiers, containing varying types of nodes, all connected by networks
which can also vary in nature depending on the tiers involved.
The device tier is at the edge. It typically contains lightweight nodes which commonly contain sensors or
actuators or user interface devices. Such devices often have limited compute and storage capabilities. The
networks used by this tier are often proximity networks, with limited bandwidth and limited range (see
[14]
6.1.2 and ISO/IEC 30141:2024, 10.2.3.2 and 10.4.1.2 for more detail about proximity networks).
The edge tier typically sits near to the device tier (where "near" is a relative term and depends on the
particular system and use case) and its role is to provide direct support to the nodes in the device tier.
One type of node in the edge tier is the gateway node, for which an IoT gateway is one example. The role
of the gateway node is to interconnect proximity networks to IP-based wide area networks. This often
involves message and protocol syntax and semantic conversions. This role includes message encryption,
deduplication and backup functions.
Another type of node in the edge tier is the control node. The control node receives data from nodes in the
device tier – typically data from sensors or input from user interface devices – and responds by issuing
instructions to other nodes in the device tier. Other types of nodes are placed in the edge tier to meet other
edge computing functional requirements. This includes management nodes, security nodes and software
support nodes.
Control nodes are usually placed in the edge tier due to issues of latency and timing. The response of a control
node is often time constrained (sometimes called real time – see Clause 14), such that the response is given
before some deadline following the receipt of some data or an event. One factor in this time constraint is the
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
transmission time of messages to and from nodes in the device tier – this leads to the need for the nodes in
the edge tier to be placed physically close to the device tier nodes and to the need to reduce the number of
hops that the messages take. These constraints can also influence the type of proximity network used and
the protocol used over those networks. Similarly, the control nodes have appropriate processing capacity
and storage for the processing that is necessary to produce appropriate and timely responses.
As an example, if the input data is a video stream from a camera device, which is a type of sensor, and the
processing required is an analysis of the video to detect the movement of some object with the intent of
influencing the movement via some actuators (which are different devices from the camera), this takes a
substantial amount of processing power and also require the handling of a substantial amount of data – the
control node have appropriate processing power and storage to successfully carry out its task.
The central tier represents a tier of nodes provided by centralized facilities. The nodes in the central tier
offer the ability to provide very substantial compute power and storage. The central tier is an excellent place
to conduct analytics or other processing that requires both a lot of compute power and access to a lot of
information. The central tier can hold large stores of information which can come from many sources – this
can be from across the other tiers or from outside locations, potentially sourced from other organizations.
The central tier can provide services to the other tiers, including services for processing data in various
ways or for holding information or providing information as required. The central tier usually has a wide
span of connectivity, meaning that it is commonly connected to many other systems, including many of the
distributed nodes in both the edge tier and in the device tier.
It is often the case that the central tier is implemented using cloud computing. A fuller description of the
relationship of edge computing to cloud computing is given in 5.4.
It is typical of the nodes in the central tier to communicate to the other tiers using high bandwidth networks,
typically the internet but possibly dedicated networks. It is also possible for the nodes in the central tier to
be arranged in a highly available resilient configuration, with multiple instances of applications and services
allied to replicated or redundant copies of information.
The tiers described in Figure 2 can become blurred when considering the many different types of devices
that are available. A significant example is the smartphone, which combines a number of elements into a
single device, as follows:
— sensors of various types, including GPS (location sensor), accelerometer, barometer, health monitors
(such as heart rate monitoring);
— camera – both for static images and video;
— microphone & loudspeaker for audio;
— display screen and user interface;
— significant compute power (e.g. quad or octo core systems, 2 Gb to 4 Gb RAM);
— significant local storage (e.g. up to 256 Gb);
— networking and connectivity.
These capabilities in a single device span the device tier and the edge tier and provide for dynamic addition
and update of software on the device, enabling a very wide range of capabilities. Combined with excellent
networking capabilities, smartphones enable some forms of edge computing in their own right – with the
added advantage of their being mobile.
5.4 Relationship of edge computing to cloud computing
Edge computing can exist on its own, without any relationship to cloud computing. In terms of the tiers
described in 5.3, systems can exist in which cloud computing is not used in any of the tiers. This implies that
the system has no need of the capabilities offered by cloud computing. Older industrial systems are of this
nature – designed to be self-contained and with fixed functionality.
© ISO/IEC 2025 – All rights reserved
ISO/IEC DTR 23188:2025(en)
However, cloud computing service or cloud computing technologies are used in one or more of the tiers. This
is especially so for the central tier – it is very common for the nodes in the central tier to be part of a cloud
computing, either a public cloud or a private cloud. Cloud computing can also be used in the edge tier – With
the emergence of small-scale high-performance hardware, it is becoming possible to use cloud c
...
ISO/IEC TS 23167:2024(E)
ISO/IEC TR DTR 23188:2024(E)
ISO/IEC JTC 1/SC 38
Secretariat: ANSI
Date: 2025-04-28
Information technology — Cloud computing — Edge computing
landscape
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ISO/IEC TS 23167 TR 23188:2024(E)
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ISO/IEC TR 23188:2024(E)
FDIS stage
4 © ISO 2019 – All rights reserved
ISO/IEC DTR 23188:(en)
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ISO/IEC DTR 23188:(en)
Contents
Foreword . ix
Introduction . x
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms . 4
5 Overview of edge computing . 5
6 Networking and edge computing . 18
7 Hardware considerations for edge computing . 20
8 Software technologies for edge computing . 22
9 Deployment models and service capabilities types and service categories for edge
computing . 25
10 Data in edge computing . 27
11 Management of edge computing . 32
12 Virtual placement . 38
13 Security and privacy in edge computing . 39
14 Real time in edge computing . 46
15 Edge computing and mobile devices . 51
Bibliography . 53
Foreword . v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Edge computing . 2
3.2 IoT terms . 2
3.3 Real time . 4
4 Symbols and abbreviated terms . 4
5 Overview of edge computing . 5
5.1 General . 5
5.2 Concepts of edge computing . 6
5.3 Architectural foundations of edge computing . 7
5.4 The relationship of edge computing to cloud computing . 9
5.5 The relationship of edge computing to IoT . 12
6 Networking and edge computing . 14
6.1 General . 14
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6.1.1 Proximity networks . 14
6.1.2 Access networks . 14
6.1.3 Services networks . 14
6.1.4 User networks . 15
6.2 Virtual networks . 15
7 Hardware considerations for edge computing . 16
7.1 General . 16
7.2 Hardware capabilities . 16
8 Software technologies for edge computing . 17
8.1 General . 17
8.2 Software classifications . 18
8.2.1 Firmware. 18
8.2.2 Platform software . 18
8.2.3 Services . 18
8.2.4 Applications . 19
8.3 Significant software technologies . 19
8.3.1 General . 19
8.3.2 Virtual machines . 19
8.3.3 Containers . 20
8.3.4 Serverless computing . 20
8.3.5 Microservices . 20
9 Deployment models and service capabilities types and service categories for edge
computing . 21
9.1 Deployment models . 21
9.2 Service model capabilities types . 21
9.3 Service categories . 22
10 Data in edge computing . 22
10.1 General . 22
10.2 Data flow . 22
10.3 Data storage . 24
10.4 Data processing . 25
11 Management of edge computing . 26
11.1 Management and orchestration fundamentals . 26
11.2 Management plane, control plane and data plane . 27
11.3 Cloud-based management and control of edge tier nodes and device tier devices . 30
11.3.1 General . 30
11.3.2 Control of services from a device . 30
11.3.3 Management of devices and edge nodes from a cloud service . 31
11.4 Orchestration and maintenance . 32
11.5 Management of data, rights and resources . 32
11.6 Security and privacy management . 32
12 Virtual placement . 32
13 Security and privacy in edge computing . 34
13.1 General . 34
13.2 Applying foundational security principles . 34
13.3 Secure nodes and devices . 35
13.4 Connectivity and network security . 36
13.5 Organization of security elements . 36
13.6 Privacy and personally identifiable information in edge computing . 39
14 Real time in edge computing . 40
14.1 Overview . 40
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14.2 Factors influencing real time system design. 41
14.3 Design approaches for real time edge computing . 44
15 Edge computing and mobile devices . 44
Bibliography . 46
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ISO/IEC DTR 23188:(en)
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are members
of ISO or IEC participate in the development of International Standards through technical committees
established by the respective organization to deal with particular fields of technical activity. ISO and IEC
technical committees collaborate in fields of mutual interest. Other international organizations, governmental
and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types of
documentsdocument should be noted. This document was drafted in accordance with the editorial rules of the
ISO/IEC Directives, Part 2 (see www.iso.org/directives www.iso.org/directives or
www.iec.ch/members_experts/refdocs).
Attention is drawnISO and IEC draw attention to the possibility that some of the elementsimplementation of
this document may beinvolve the subjectuse of (a) patent(s). ISO and IEC take no position concerning the
evidence, validity or applicability of any claimed patent rights. in respect thereof. As of the date of publication
of this document, ISO and IEC had not received notice of (a) patent(s) which may be required to implement
this document. However, implementers are cautioned that this may not represent the latest information,
which may be obtained from the patent database available at www.iso.org/patents and https://patents.iec.ch.
ISO and IEC shall not be held responsible for identifying any or all such patent rights. Details of any patent
rights identified during the development of the document will be in the Introduction and/or on the ISO list of
patent declarations received (see www.iso.org/patents) or the IEC list of patent declarations received (see
http://patents.iec.ch).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/iso/foreword.html.
www.iso.org/iso/foreword.html. In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 38, Cloud computing and distributed platforms.
This second edition cancels and replaces the first edition (ISO/IEC 23188:2020), which has been technically
revised.
The main changes are as follows:
— this document has been aligned with the ISO/IEC 22123 series;
— reference to ISO/IEC 17788 and ISO/IEC 17789 have been changed to the ISO/IEC 22123 series;
— verbal forms have been updated in line with the ISO/IEC Directives Part 2.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.htmlwww.iso.org/members.html and
www.iec.ch/national-committees.
© ISO/IEC 2025 – All rights reserved
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ISO/IEC DTR 23188:(en)
Introduction
Edge computing is increasingly used in systems that deal with aspects of the physical world. Edge computing
involves the placement of processing and storage near or at the places where those systems interact with the
physical world, which is where the "edge" exists. One of the trends in this space is the development of
increasingly capable Internet of Things (IoT) devices (sensors and actuators), which generate more data or
new types of data. There is significant benefit from moving the processing and storing of this data close to the
place where the data is generated.
Cloud computing is commonly used in systems that are based on edge computing approaches. This can include
the connection of both devices and edge computing nodes to centralized cloud services. However, it is the case
that the locations in which cloud computing is performed are increasingly distributed in nature. The cloud
services are being implemented in locations that are nearer to the edge in order to support use cases that
demand reduced latency or avoiding the need to transmit large volumes of data over networks with limited
bandwidth.
This document aims to describe edge computing and the significant elements which contribute to the
successful implementation of edge computing systems, with an emphasis on the use of cloud computing and
cloud computing technologies in the context of edge computing, including the virtualization of compute,
storage and networking resources.
[18] [ ]
It is useful to read this document in conjunction with ISO/IEC TR 30164 ,, 0 which takes a view of edge
computing from the point of view of IoT systems and the IoT devices which interact with the physical world.
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Information technology — Cloud computing — Edge computing
landscape
1 Scope
This document examines the concept of edge computing, its relationship to cloud computing and IoT, and the
technologies that are key to the implementation of edge computing. This document explores the following
topics with respect to edge computing:
— — concept of edge computing systems;
— — architectural foundation of edge computing;
— — edge computing terminology;
— — software classifications in edge computing, e.g.,. firmware, services, applications;
— — supporting technologies, e.g.,. containers, serverless computing, microservices;
— — networking for edge computing systems, including virtual networks;
— — data, e.g.,. data flow, data storage, data processing;
— — management, of software, of data and of networks, resources, quality of service;
— — virtual placement of software and data, and metadata;
— — security and privacy;
— — real time;
— — mobile edge computing, mobile devices.
2 Normative references
There are no normative references in this document.
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 22123-1, Information technology — Cloud computing — Part 1: Vocabulary
ISO/IEC 23167, Information technology — Cloud computing — Common technologies and techniques
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 22123-1, ISO/IEC TS 23167 and
the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
— — ISO Online browsing platform: available at http://www.iso.org/obphttps://www.iso.org/obp
— — IEC Electropedia: available at http://www.electropedia.org/https://www.electropedia.org/
3.1 Edge computing
3.1.1 3.1.1
distributed computing
model of computing in which a set of nodes (3.1.5)(3.1.5) coordinates its activities by means of digital
messages passed between the nodes (3.1.5)
3.1.2 3.1.2
edge
boundary between pertinent digital and physical entities (3.2.8),(3.2.8), delineated by networked sensors
(3.2.9)(3.2.9) and actuators (3.2.1)(3.2.1)
Note 1 to entry: Pertinent digital entities means that the digital entities which need to be considered can vary depending
on the system under consideration and the context in which those entities are used. See 5.2See 5.2 for more detail.
3.1.3 3.1.3
edge computing
distributed computing (3.1.1)(3.1.1) in which processing and storage takes place at or near the edge
(3.1.2),(3.1.2), where the nearness is defined by the system's requirements
3.1.4 3.1.4
lightweight node
node (3.1.5)(3.1.5) with limited processing, storage and networking capacities
3.1.5 3.1.5
node
networked machine with processing and storage capabilities
3.1.6 3.1.6
edge computing system
system providing functionalities of edge computing (3.1.3)(3.1.3)
3.1.7 3.1.7
endpoint
combination of a binding and a network address
[SOURCE: ISO/TR 24097-3:2019, 3.4]
3.2 IoT terms
3.2.1 3.2.1
actuator
IoT device (3.2.4)(3.2.4) that changes one or more properties of a physical entity (3.2.8)(3.2.8) in response to
a valid input
[SOURCE: ISO/IEC 20924:2024, 3.2.2]
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ISO/IEC DTR 23188:(en)
3.2.2 3.2.2
Internet of Things
IoT
infrastructure of interconnected entities, people, systems and information resources together with services
which processes and reacts to information from the physical world and virtual world
[SOURCE: ISO/IEC 20924:2024, 3.2.8]
3.2.3 3.2.3
Internet Protocol
IP
protocol specified in RFC 791 (IP version 4) or in RFC 2460 (IP version 6)
[SOURCE: ISO/IEC TR 21890:2001, 3.4]
3.2.4 3.2.4
IoT device
entity of an IoT system (3.2.6)(3.2.6) that interacts and communicates with the physical world through sensing
or actuating
Note 1 to entry: An IoT device (3.2.4)(3.2.4) can be a sensor (3.2.9)(3.2.9) or an actuator (3.2.1).(3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.11]
3.2.5 3.2.5
IoT gateway
entity of an IoT system (3.2.6)(3.2.6) that connects one or more proximity networks and the IoT devices
(3.2.4)(3.2.4) on those networks to each other and to one or more access networks
[SOURCE: ISO/IEC 20924:2024, 3.2.14]
3.2.6 3.2.6
IoT system
system providing functionalities of Internet of Things (3.2.2)(3.2.2)
Note 1 to entry: IoT system is inclusive of IoT devices (3.2.4),(3.2.4), IoT gateways (3.2.5),(3.2.5), sensors (3.2.9),(3.2.9),
and actuators (3.2.1).(3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.15]
3.2.7 3.2.7
operational technology
OT
hardware and software that detects or causes a change through the direct monitoring and/or control of
physical devices and systems, processes and events in the organization
3.2.8 3.2.8
physical entity
entity that has material existence in the physical world
[SOURCE: ISO/IEC 20924:2024, 3.1.25]
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ISO/IEC DTR 23188:(en)
3.2.9 3.2.9
sensor
IoT device (3.2.4)(3.2.4) that measures one or more properties of one or more physical entities (3.2.8)(3.2.8)
and outputs digital data that can be transmitted over a network
[SOURCE: ISO/IEC 20924:2024, 3.2.20]
3.3 Real time
3.3.1 3.3.1
real time
processing of data by a computer in connection with another process outside the computer according to time
requirements imposed by the outside process
[SOURCE: ISO/IEC 2382:2015, 2122900, modified: — words 'pertaining to' removed to improve
substitutability of definition; Notes 1 to 3 to entry have been removed.]
3.3.2 3.3.2
real time system
system in which processing meets real time (3.3.1)(3.3.1) requirements
3.3.3 3.3.3
hard real time system
real time system (3.3.2)(3.3.2) whose operation is incorrect if results are not produced according to specified
timing requirements
3.3.4 3.3.4
soft real time system
real time system (3.3.2)(3.3.2) whose operation is degraded if results are not produced according to specified
timing requirements
4 Symbols and abbreviated terms
AC Alternating current
BYOD Bring Your Own Device
CDN Content Distribution Network
CSC Cloud service customer
CSP Cloud service provider
CSU Cloud service user
CSU Cloud service user
DDoS Distributed Denial of Service
DDoS Distributed Denial of Service
DevSecOps Development, Security, and Operations
EPG Electronic Programme Guide
EPROM Erasable Programmable Read Only Memory
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ISO/IEC DTR 23188:(en)
FPGA Field Programmable Gate Array
Gb Gigabyte
GPS Global Positioning System
GPU Graphics Processing Unit
IETF Internet Engineering Task Force
IoT Internet of Things
IP Internet Protocol
IPTV Internet Protocol television
LAN Local Area Network
MDM Mobile Device Management
OS Operating system
PC Personal Computer
PII Personally Identifiable Information
RAM Random-access Memory
RFC Request for Comments
ROM Read Only Memory
TPM Trusted Platform Module
VM Virtual Machine
VoIP Voice over Internet Protocol
VPN Virtual Private Network
WiFi Wireless Fidelity
WiFi Wireless Fidelity
5 Overview of edge computing
5.1 General
Over time, the forms of computing have varied between centralized and distributed, depending on the nature
and capabilities of the computing devices and of the networks used to connect them.
Mainframe computers represent a form of centralised computing, where the main computer systems are
placed in a data centre, containing processing and storage units. Originally, almost the whole of the computing
system was situated within the data centre. Gradually, time-sharing terminals were located in remote
locations to provide user access to the mainframe systems. Terminals were typically little more than a display
with a keyboard for input and the associated network connection had limited bandwidth, perhaps involving a
dial-up modem.
The personal computer (PC) represents a distributed form of computing. The PC has significant processing
and storage capabilities and can be used very effectively in a standalone mode. However, PCs are more
typically used in a networked mode. Initially, the networks were used for simple communications such as (text
based) email, but as the network bandwidth increased over time, increasingly sophisticated activities took
place, with file transfer and eventually peer-to-peer capabilities being used.
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ISO/IEC DTR 23188:(en)
The availability of higher bandwidth networking encouraged the development of the client-server
architecture, with the PC used for the client, connected to a centralized server which performs the main
processing and storage. Client can include quite substantial software elements performing significant
processing activities. Data might also be stored locally for faster access, although the main database(s) are
held centrally.
The advent of the internet and the World Wide Web (WWW) represents the appearance of another form of
computing. In this form of computing, web servers serve up web pages and related material which are
accessed through client web browsers. Devices running web browsers can be relatively low in compute power,
while the web servers for some of the more popular and high demand web sites can involve massive compute
power spread over many machines in a large data centre.
Cloud computing is a computing paradigm that provides various types of computing resources on demand in
a highly scalable manner through cloud computing services. In practice, it relies on a highly centralized
architecture, with computing resources concentrated in large data centerscentres. However, cloud computing
also incorporates certain features of distributed computing. It is common for cloud service providers to
operate multiple physically separated data centerscentres, and cloud service users (CSUs) often use
applications and data to be distributed across these centerscentres using cloud computing service– for
resilience, to reduce latency and for disaster recovery purposes. In addition, the favoured design paradigm for
cloud native applications is to distribute multiple instances of each application component across different
machines within the cloud computing system. This design paradigm and the technologies that support it are
of significance to edge computing.
5.2 Concepts of edge computing
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities, i.e.,.
between the digital system and the physical world, delineated by networked sensors and actuators. The
concept of edge computing is shown in Figure 1.Figure 1.
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
Figure 1 — The concept — Concept of edge computing
Pertinent digital entities meansmean that the digital entities which need to be considered can vary depending
on the system under consideration and the context in which those entities are used.
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
An example of varying pertinence are the servers within a cloud computing data centre. When CSCs use cloud
services deployed on such servers to build IoT systems, it is difficult to say that the location of IoT sensors is
always 'atat the edge. However, from the perspective of the CSPs having to manage the cloud computing data
centre, it is highly likely that the servers are instrumented with a variety of sensors capable of reporting
various physical properties of the servers, for example their temperature. Those sensors are at the edge.
Nearness for edge computing is usually based on minimising the latency for communication between the IoT
devices that are at the edge and the place(s) where data processing and storage occurs. Nearness can mean
placing the edge computing nodes physically close to the IoT devices. In the most extreme cases, nearness
means combining the sensors and actuators and edge computing into a single node, as might happen with a
smart phone. In other cases, the edge computing nodes are separated from the IoT devices but are placed
physically close to the IoT devices and have a proximity network connecting them designed to minimise
latency. Nearness can also be influenced by the nature of the networks and the volume of data flowing to and
from the IoT devices – where large volumes of data and high data rates are involved, edge nodes are placed so
as to reduce the latency of handling this data to the minimum necessary to meet the requirements of the use
case.
Digital systems can observe and affect the physical world. Sensors and actuators are at the edge between the
digital systems and the physical world. Edge computing systems generally combine these IoT devices with
distributed computing resources to provide the capabilities of the system. In edge computing systems, actions
often need to occur within specific timeframes, i.e. edge computing systems can also be real time systems, and
latency considerations affect system design and the choice of the placement of data processing and storage to
achieve timing requirements. Edge computing helps to meet those timing requirements.
Edge computing is characterized by networked systems in which significant data processing and storage takes
place on nodes near the edge, rather than in some centralized location. Edge computing can be contrasted with
centralized computing where the centralized nodes are remote from the edge. However, it is important to note
that edge computing is complementary to centralized forms of computing and that in any given system, edge
computing is often used in conjunction with centralized computing.
There are multiple reasons for the rise in the use of edge computing. One reason is the arrival of new devices
combining significant processing power and storage with low power usage. Smart phones have been one of
the driving factors in this area, with billions of such devices in daily use. The Internet of Things (IoT) is another
reason, with small, low power, low cost IoT devices enabling the creation of IT systems which can sense and
act on real world entities.
5.3 Architectural foundations of edge computing
Edge computing involves nodes that are highly heterogeneous, and which are commonly arranged in tiers of
compute and storage capabilities. A simplified view of the organization of edge computing nodes and the
networks connecting them in edge computing is shown in Figure 2.Figure 2.
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
Figure 2 — Organization of nodes in edge computing
The tiers shown in Figure 2Figure 2 are essentially a conceptual model (containing physical elements) and are
illustrative rather than definitive – in reality the number of tiers and the type of node in each tier and the
networks connecting them are variable, depending on the nature of the system involved. What is important to
understand is that there are multiple tiers, containing varying types of nodes, all connected by networks which
can also vary in nature depending on the tiers involved.
The device tier is at the edge. It typically contains lightweight nodes which commonly contain sensors or
actuators or user interface devices. Such devices often have limited compute and storage capabilities. The
networks used by this tier are often proximity networks, with limited bandwidth and limited range (see 6.1.1
[2] [ ]
in this document and ISO/IEC 30141:2024 ,6.1.2 and ISO/IEC 30141:2024, 0 10.2.3.2 and 10.4.1.2 for more
detail about proximity networks).
The edge tier typically sits near to the device tier (where "near" is a relative term and depends on the particular
system and use case) and its role is to provide direct support to the nodes in the device tier. One type of node
in the edge tier is the gateway node, for which an IoT gateway is one example. The role of the gateway node is
to interconnect proximity networks to IP-based wide area networks. This often involves message and protocol
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
syntax and semantic conversions. This role includeincludes message encryption, deduplication and backup
functions.
Another type of node in the edge tier is the control node. The control node receives data from nodes in the
device tier – typically data from sensors or input from user interface devices – and responds by issuing
instructions to other nodes in the device tier. Other types of nodes are placed in the edge tier to meet other
edge computing functional requirements. This includes management nodes, security nodes and software
support nodes.
Control nodes are usually placed in the edge tier due to issues of latency and timing. The response of a control
node is often time constrained (sometimes called real time – see Clause 14),14), such that the response is
given before some deadline following the receipt of some data or an event. One factor in this time constraint
is the transmission time of messages to and from nodes in the device tier – this leads to the need for the nodes
in the edge tier to be placed physically close to the device tier nodes and to the need to reduce the number of
hops that the messages take. These constraints can also influence the type of proximity network used and the
protocol used over those networks. Similarly, the control nodes have appropriate processing capacity and
storage for the processing that is necessary to produce appropriate and timely responses.
As an example, if the input data is a video stream from a camera device, which is a type of sensor, and the
processing required is an analysis of the video to detect the movement of some object with the intent of
influencing the movement via some actuators (which are different devices from the camera), this takes a
substantial amount of processing power and also require the handling of a substantial amount of data – the
control node have appropriate processing power and storage to successfully carry out its task.
The central tier represents a tier of nodes provided by centralized facilities. The nodes in the central tier offer
the ability to provide very substantial compute power and storage. The central tier is an excellent place to
conduct analytics or other processing that requires both a lot of compute power and access to a lot of
information. The central tier can hold large stores of information which can come from many sources – this
can be from across the other tiers or from outside locations, potentially sourced from other organizations. The
central tier can provide services to the other tiers, including services for processing data in various ways or
for holding information or providing information as required. The central tier usually has a wide span of
connectivity, meaning that it is commonly connected to many other systems, including many of the distributed
nodes in both the edge tier and in the device tier.
It is often the case that the central tier is implemented using cloud computing. A fuller description of the
relationship of edge computing to cloud computing is given in 5.4.5.4.
It is typical of the nodes in the central tier to communicate to the other tiers using high bandwidth networks,
typically the internet but possibly dedicated networks. It is also possible for the nodes in the central tier to be
arranged in a highly available resilient configuration, with multiple instances of applications and services
allied to replicated or redundant copies of information.
The tiers described in Figure 2Figure 2 can become blurred when considering the many different types of
devices that are available. A significant example is the smartphone, which combines a number of elements into
a single device, as follows:
— — sensors of various types, including GPS (location sensor), accelerometer, barometer, health monitors
(such as heart rate monitoring);
— — camera – both for static images and video;
— — microphone & loudspeaker for audio;
© ISO/IEC 2024 2025 – All rights reserved
ISO/IEC DTR 23188:(en)
— — display screen and user interface;
— — significant compute power (e.g.,. quad or octo core systems, 2 Gb to 4 Gb RAM);
— — significant local storage (e.g.,. up to 256 Gb);
— — networking and connectivity.
These capabilities in a single device span the device tier and the edge tier and provide for dynamic addition
and update of software on the device, enabling a very wide range of capabilities. Combined with excellent
networking capabilities, smartphones enable some forms of edge computing in their own right – with the
added advantage of their being mobile.
5.4 The relationshipRelationship of edge computing to cloud computing
Edge computing can exist on its own, without any relationship to cloud computing. In terms of the tiers
described in 5.3,5.3, systems can exist in which cloud computing is not used in any of the tiers. This implies
that the system has no need of the capabilities offered by cloud computing. Older industrial systems are of this
nature – designed to be self-contained and with fixed functionality.
However, cloud computing service or cloud computing technologies are used in one or more of the tiers. This
is especially so for the central tier – it is very common for the nodes in the central tier to be part of a cloud
computing, either a public cloud or a private cloud. Cloud computing can also be used in the edge tier – With
the emergence of small-scale high-performance hardware, it is becoming possible to use cloud computing at
the edge tier. Although today use of cloud computing in the device tier is unusual and rare, there is nothing in
principle to preclude its use once the device nodes are sufficiently powerful and well-connected.
It is worth noting that edge computing rarely exists on its own, but is connected to both processing and
information which is held in the central tier. This means systems have processing and storage spread right
across the various tiers and types of nodes. The principle is the right placement of processing and storage
elements. Right placement in that processing and storage take place on nodes that are best suited to the task
involved.
Figure 3Figure 3 illustrates how IoT devices and edge computing can relate to different parts of the cloud
computing ecosystem. This can include cloud services built on a private cloud (both on-premises and more
remotely) and a public cloud (including public clouds designed to s
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Technical
Report
ISO/IEC DTR
23188.2
ISO/IEC JTC 1/SC 38
Information technology — Cloud
Secretariat: ANSI
computing — Edge computing
Voting begins on:
landscape
2025-11-24
Technologies de l'information — Informatique en nuage —
Voting terminates on:
Environnement de l'edge computing
2025-12-22
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Reference number
FINAL DRAFT
Technical
Report
ISO/IEC DTR
23188.2
ISO/IEC JTC 1/SC 38
Information technology — Cloud
Secretariat: ANSI
computing — Edge computing
Voting begins on:
landscape
Technologies de l'information — Informatique en nuage —
Voting terminates on:
Environnement de l'edge computing
RECIPIENTS OF THIS DRAFT ARE INVITED TO SUBMIT,
WITH THEIR COMMENTS, NOTIFICATION OF ANY
RELEVANT PATENT RIGHTS OF WHICH THEY ARE AWARE
AND TO PROVIDE SUPPOR TING DOCUMENTATION.
© ISO/IEC 2025
IN ADDITION TO THEIR EVALUATION AS
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO
LOGICAL, COMMERCIAL AND USER PURPOSES, DRAFT
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
INTERNATIONAL STANDARDS MAY ON OCCASION HAVE
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
TO BE CONSIDERED IN THE LIGHT OF THEIR POTENTIAL
or ISO’s member body in the country of the requester.
TO BECOME STAN DARDS TO WHICH REFERENCE MAY BE
MADE IN NATIONAL REGULATIONS.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: +41 22 749 01 11
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland Reference number
© ISO/IEC 2025 – All rights reserved
ii
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Edge computing .2
3.2 IoT terms .3
3.3 Real time .4
3.4 Cloud computing .4
4 Symbols and abbreviated terms. 5
5 Overview of edge computing . . 6
5.1 General .6
5.2 Concepts of edge computing .6
5.3 Architectural foundations of edge computing .8
5.4 Relationship of edge computing to cloud computing .10
5.5 Relationship of edge computing to IoT . 12
6 Networking and edge computing . 14
6.1 General .14
6.1.1 Overview .14
6.1.2 Proximity networks.14
6.1.3 Access networks .14
6.1.4 Services networks .14
6.1.5 User networks . 15
6.2 Virtual networks. 15
7 Hardware considerations for edge solution .16
7.1 General .16
7.2 Hardware capabilities .16
8 Software technologies for edge solution . 17
8.1 General .17
8.2 Software classifications .17
8.2.1 Firmware . .17
8.2.2 Platform software .18
8.2.3 Services .18
8.2.4 Application .18
8.3 Significant software technologies .19
8.3.1 General .19
8.3.2 Virtual machines .19
8.3.3 Containers .19
8.3.4 Serverless computing . 20
8.3.5 Microservices . 20
9 Deployment models and service capabilities types and service categories for edge
computing . .20
9.1 General . 20
9.2 Deployment models . 20
9.3 Service capabilities types .21
9.4 Service categories .21
10 Data in edge computing .21
10.1 General .21
10.2 Data flow . 22
10.3 Data storage . 23
10.4 Data processing.24
© ISO/IEC 2025 – All rights reserved
iii
11 Management of edge computing systems .25
11.1 Management and orchestration fundamentals . 25
11.2 Management plane, control plane and data plane . 26
11.3 Cloud-based management and control of edge tier nodes and device tier devices . 28
11.3.1 General . 28
11.3.2 Control of services from a device . 28
11.3.3 Management of devices and edge nodes from a cloud service . 29
11.4 Orchestration and maintenance . 29
11.5 Management of data, rights and resources . 29
11.6 Security and privacy management . 30
12 Virtual placement .30
13 Security and privacy in edge computing .31
13.1 General .31
13.2 Applying foundational security principles .32
13.3 Secure nodes and devices .32
13.4 Connectivity and network security . 33
13.5 Organization of security elements . 34
13.5.1 General . 34
13.5.2 Network security . 34
13.5.3 Data security . 35
13.5.4 Application security . 35
13.5.5 Node security . 35
13.5.6 Security OSS . 36
13.6 Privacy and personally identifiable information in edge computing . 36
14 Real time in edge computing .37
14.1 General .37
14.2 Factors influencing real time system design .37
14.3 Design approaches for real time edge computing . 40
15 Edge computing and mobile devices .40
Bibliography .42
© ISO/IEC 2025 – All rights reserved
iv
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical activity.
ISO and IEC technical committees collaborate in fields of mutual interest. Other international organizations,
governmental and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types
of document should be noted. This document was drafted in accordance with the editorial rules of the ISO/
IEC Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the
use of (a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any
claimed patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had not
received notice of (a) patent(s) which may be required to implement this document. However, implementers
are cautioned that this may not represent the latest information, which may be obtained from the patent
database available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held
responsible for identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/iso/foreword.html.
In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 38, Cloud computing and distributed platforms.
This second edition cancels and replaces the first edition (ISO/IEC 23188:2020), which has been technically
revised.
The main changes are as follows:
— this document has been aligned with the ISO/IEC 22123 series;
— reference to ISO/IEC 17788 and ISO/IEC 17789 have been changed to the ISO/IEC 22123 series;
— verbal forms have been updated in line with the ISO/IEC Directives Part 2.
Any feedback or questions on this document should be directed to the user’s national standards
body. A complete listing of these bodies can be found at www.iso.org/members.html and
www.iec.ch/national-committees.
© ISO/IEC 2025 – All rights reserved
v
Introduction
Edge computing is increasingly used in systems that deal with aspects of the physical world. Edge computing
involves the placement of processing and storage near or at the points where those systems interact with
the physical world, which is where the "edge" exists. One of the trends is the development of increasingly
capable Internet of Things (IoT) devices (sensors and actuators), which generate more data or new types
of data. There is significant benefit from moving the processing and storing of this data closer to where the
data is generated.
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities, i.e.
between the digital system and the physical world, delineated by networked sensors and actuators.
Pertinent digital entities mean that the digital entities which need to be considered can vary depending on
the system under consideration and the context in which those entities are used.
Modern systems such as those for IoT and OT applications include both cloud services and edge services.
This can include the connection of both end-user devices and edge computing nodes to centralized cloud
services. It is also the case that cloud service provision is increasingly distributed. Cloud services are
being implemented in nodes that are closer to the end user in order to support reduced latency or to avoid
transferring large volumes of data over expensive networks.
This document aims to describe edge computing and the significant elements which contribute to the
successful implementation of edge computing systems, with an emphasis on the use of cloud computing and
cloud computing technologies in the context of edge computing, including the virtualization of compute,
storage and networking resources.
This document is intended to be used in conjunction with ISO/IEC TR 30164, which takes a view of edge
computing from the point of view of IoT systems and the IoT devices which interact with the physical world.
© ISO/IEC 2025 – All rights reserved
vi
FINAL DRAFT Technical Report ISO/IEC DTR 23188.2:2025(en)
Information technology — Cloud computing — Edge
computing landscape
1 Scope
This document examines the concept of edge computing, its relationship to cloud computing and IoT, and the
technologies that are key to the implementation of edge computing. This document explores the following
topics with respect to edge computing:
— concept of edge computing systems;
— architectural foundation of edge computing;
— edge computing terminology;
— software classifications in edge computing, e.g. firmware, services, applications;
— supporting technologies, e.g. containers, serverless computing, microservices;
— networking for edge computing systems, including virtual networks;
— data, e.g. data flow, data storage, data processing;
— management, of software, of data and of networks, resources, quality of service;
— virtual placement of software and data, and metadata;
— security and privacy;
— real time operation;
— mobile edge computing, mobile devices.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 22123-1, Information technology — Cloud computing — Part 1: Vocabulary
ISO/IEC TS 23167, Information technology — Cloud computing — Common technologies and techniques
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 22123-1, ISO/IEC TS 23167
and the following apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
© ISO/IEC 2025 – All rights reserved
3.1 Edge computing
3.1.1
distributed computing
model of computing in which a set of nodes (3.1.9) coordinates its activities by means of digital messages
passed between the nodes
3.1.2
edge
boundary between pertinent digitalentities (3.2.2) and physical entities (3.2.8), delineated by sensors (3.2.9)
and actuators (3.2.1)
Note 1 to entry: Pertinent digital entities means that the digital entities which need to be considered can vary
depending on the system under consideration and the context in which those entities are used.
Note 2 to entry: Pertinent physical entities can include devices other than sensors and actuators.
Note 3 to entry: The edge can be placed at the edge end or the device end of the proximity network connecting them,
often depending on who owns or operates the proximity network.
3.1.3
edge computing
distributed computing (3.1.1) in which some or all processing and storage takes place at or near the edge
(3.1.2), where the nearness is defined by the system's requirements
3.1.4
edge computing service
one or more capabilities offered via edge computing (3.1.3) invoked using a defined interface
3.1.5
edge computing system
system providing functionalities of edge computing (3.1.3)
Note 1 to entry: Edge computing systems to include capabilities for both edge computing and cloud computing
3.1.6
edge computing user
ECU
user of edge computing system (3.1.5)
3.1.7
edge solution
edge computing services (3.1.4) combined and controlled to meet edge computing user‘s (3.1.6) requirements.
3.1.8
endpoint
entity (3.2.4) that exposes and uses one or more network interfaces.
Note 1 to entry: An endpoint includes any hardware device that is capable of sending or receiving data over a network.
[SOURCE: ISO/IEC 20924:2024, 3.1.15, modified — In the definition, "component" has been replaced by
"entity" to broaden the scope.]
3.1.9
node
networked machine with processing and storage capabilities
Note 1 to entry: Both digital and physical entities are examples of nodes. Virtual machine or container in cloud solution
would also be a node.
© ISO/IEC 2025 – All rights reserved
3.1.10
operational technology
OT
hardware and software that detects or causes a change through the direct monitoring and/or control of
physical devices and systems, processes and events in the organization
3.2 IoT terms
3.2.1
actuator
IoT device (3.2.5) that changes one or more properties of a physical entity (3.2.8) in response to an input
[SOURCE: ISO/IEC 20924:2024, 3.2.2]
3.2.2
digital entity
entity (3.2.3) that exists in the digital realm
Note 1 to entry: A digital entity can exist in several forms, including a cloud service (3.4.2) or X as a service in a data
centre, or as a network element or as an IoT gateway (3.2.6).
[SOURCE: ISO/IEC 20924:2024, 3.1.13]
3.2.3
entity
anything (physical or non-physical) having a distinct existence
[SOURCE: ISO/IEC 15459-3:2014, 3.1]
3.2.4
Internet of Things
IoT
infrastructure of interconnected entities, people, systems and information resources together with services
which processes and reacts to information from the physical world and virtual world
[SOURCE: ISO/IEC 20924:2024, 3.2.8]
3.2.5
IoT device
endpoint (3.1.8) that interacts with the physical world through sensing or actuating
Note 1 to entry: An IoT device (3.2.5) can be a sensor (3.2.9) or an actuator (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.11]
3.2.6
IoT gateway
entity of an IoT system (3.2.7) that connects one or more proximity networks and the IoT devices (3.2.5) on
those networks to each other and to one or more access networks
[SOURCE: ISO/IEC 20924:2024, 3.2.14]
3.2.7
IoT system
system providing functionalities of Internet of Things (3.2.4)
Note 1 to entry: IoT system is inclusive of IoT devices (3.2.5), IoT gateways (3.2.6), sensors (3.2.9), and actuators (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.15]
© ISO/IEC 2025 – All rights reserved
3.2.8
physical entity
entity in the physical world that can be the subject of sensing and/or actuating
[SOURCE: ISO/IEC 20924:2024, 3.1.25]
3.2.9
sensor
IoT device (3.2.5)with the capability of sensing
[SOURCE: ISO/IEC 20924:2024, 3.2.20]
3.3 Real time
3.3.1
real time
processing of data by a computer in connection with another process outside the computer according to
time requirements imposed by the outside process
[SOURCE: ISO/IEC 2382:2015, 2122900, modified — "pertaining to" has been removed to improve
substitutability of definition; Notes 1 to 3 to entry have been removed.]
3.3.2
real time system
system in which processing meets real time (3.3.1) requirements
3.3.3
hard real time
real time system (3.3.2) whose operation is incorrect if results are not produced according to specified
timing requirements
3.3.4
soft real time
real time system (3.3.2) whose operation is degraded if results are not produced according to specified
timing requirements
3.4 Cloud computing
3.4.1
cloud computing
paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources
with self-service provisioning and administration on demand
[SOURCE: ISO/IEC 22123-1:2023, 3.1.1, modified — Notes 1 and 2 to entry have been deleted.]
3.4.2
cloud service
one or more capabilities offered via cloud computing (3.4.1) invoked using a defined interface
© ISO/IEC 2025 – All rights reserved
4 Symbols and abbreviated terms
AC Alternating current
BYOD Bring Your Own Device
CDN Content Distribution Network
CPU Central Processing Unit
CSC Cloud service customer
CSP Cloud service provider
CSU Cloud service user
DDoS Distributed Denial of Service
DevSecOps Development, Security, and Operations
ECU Edge computing user
EPG Electronic Programme Guide
EPROM Erasable Programmable Read Only Memory
FPGA Field Programmable Gate Array
GPS Global Positioning System
GPU Graphics Processing Unit
ID Identity
IETF Internet Engineering Task Force
IoT Internet of Things
IP Internet Protocol
IPTV Internet Protocol television
LAN Local Area Network
MDM Mobile Device Management
OS Operating system
OSS Operations Support System
PC Personal Computer
PII Personally Identifiable Information
RAM Random-access Memory
RFC Request for Comments
ROM Read Only Memory
SIM Subscriber Identity Module
© ISO/IEC 2025 – All rights reserved
TPM Trusted Platform Module
VM Virtual Machine
VoIP Voice over Internet Protocol
VPN Virtual Private Network
WiFi Wireless Fidelity
5 Overview of edge computing
5.1 General
Over time, the forms of computing have varied between centralized and distributed, depending on the
nature and capabilities of the computing devices and of the networks used to connect them.
Mainframe computers represent a form of centralised computing, where the main computer systems
are placed in a data centre, containing processing and storage units. Originally, almost the whole of the
computing system was situated within the data centre. Gradually, time-sharing terminals were located in
remote locations to provide user access to the mainframe systems. Terminals were typically little more than
a display with a keyboard for input and the associated network connection had limited bandwidth, perhaps
involving a dial-up modem.
The personal computer (PC) represents a distributed form of computing. The PC has significant processing
and storage capabilities and can be used very effectively in a standalone mode. However, PCs are more
typically used in a networked mode. Initially, the networks were used for simple communications such as
(text based) email, but as the network bandwidth increased over time, increasingly sophisticated activities
took place, with file transfer and eventually peer-to-peer capabilities being used.
The availability of higher bandwidth networking encouraged the development of the client-server
architecture, with the PC used for the clients, connected to a centralized server which performs the main
processing and storage. Clients can include quite substantial software elements performing significant
processing activities. Data can also be stored locally for faster access, although the main database(s) are
held centrally.
The advent of the internet and the World Wide Web (WWW) represents the appearance of another form
of computing. In this form of computing, web servers serve up web pages and related material which are
accessed through client’s web browsers. Devices running web browsers can be relatively low in compute
power, while the web servers for some of the more popular and high demand web sites can involve massive
compute power spread over many machines in a large data centre.
Cloud computing is a computing paradigm that provides various types of computing resources on demand
in a highly scalable manner through cloud computing services. In practice, it relies on a highly centralized
architecture, with computing resources concentrated in large data centres. However, cloud computing also
incorporates certain features of distributed computing. It is common for cloud service providers to operate
multiple physically separated data centres, and cloud service users (CSUs) often use applications and data
to be distributed across these centres using cloud computing service – for resilience, to reduce latency and
for disaster recovery purposes. In addition, the favoured design paradigm for cloud native applications is
to distribute multiple instances of each application component across different machines within the cloud
computing system. This design paradigm and the technologies that support it are of significance to edge
computing.
5.2 Concepts of edge computing
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities,
i.e. between the digital system and the physical world, delineated by networked sensors and actuators. The
concept of edge computing is shown in Figure 1.
© ISO/IEC 2025 – All rights reserved
Figure 1 — Concept of edge computing
Pertinent digital entities mean that the digital entities which need to be considered can vary depending on
the system under consideration and the context in which those entities are used.
An example of varying pertinence are the servers within a cloud computing data centre. When cloud service
customers (CSCs) use cloud services deployed on such servers to build IoT systems, it is difficult to say
that the location of IoT sensors is always at the edge. However, from the perspective of the cloud service
providers (CSPs) having to manage the cloud computing data centre, it is highly likely that the servers are
instrumented with a variety of sensors capable of reporting various physical properties of the servers, for
example their temperature. Those sensors are at the edge.
Nearness for edge computing is usually based on minimising the latency for communication between the IoT
devices that are at the edge and the place(s) where data processing and storage occurs. Nearness can mean
placing the edge computing nodes physically close to the IoT devices or near the communication network
nodes connect the IoT devices to data centres or the places where data processing and storage occurs. In the
most extreme cases, nearness means combining the sensors and actuators and edge computing into a single
node, as will possibly happen with a smart phone. In other cases, the edge computing nodes are separated
from the IoT devices but are placed physically close to the IoT devices and have a proximity network
connecting them or close to communication network nodes connected IoT devices to minimise latency.
Nearness can also be influenced by the nature of the networks and the volume of data flowing to and from
the IoT devices – where large volumes of data and high data rates are involved, edge nodes are placed so as to
reduce the latency of handling this data to the minimum necessary to meet the requirements of the use case.
Digital systems can observe and affect the physical world. Sensors and actuators are at the edge between
the digital systems and the physical world. Edge computing systems generally combine these IoT devices
with distributed computing resources to provide the capabilities of the system. In edge computing systems,
actions often need to occur within specific timeframes, i.e. edge computing systems can also be real time
systems, and latency considerations affect system design and the choice of the placement of data processing
and storage to achieve timing requirements. Edge computing helps to meet those timing requirements.
Edge computing is characterized by networked systems in which significant data processing and storage
takes place on nodes near the edge, rather than in some centralized location. Edge computing can be
contrasted with centralized computing where the centralized nodes are remote from the edge. However,
© ISO/IEC 2025 – All rights reserved
edge computing is complementary to centralized forms of computing and in any given system, edge
computing is often used in conjunction with centralized computing.
There are multiple reasons for the rise in the use of edge computing. One reason is the arrival of new devices
combining significant processing power and storage with low power usage. Smart phones have been one
of the driving factors in this area, with billions of such devices in daily use. The Internet of Things (IoT) is
another reason, with small, low power, low cost IoT devices enabling the creation of IT systems which can
sense and act on real world entities.
5.3 Architectural foundations of edge computing
Edge computing involves nodes that are commonly arranged in tiers of compute and storage capabilities.
They can be highly heterogeneous both within a tier and across different tiers. A simplified view of the
organization of edge computing nodes and the networks connecting them in edge computing is shown in
Figure 2.
Figure 2 — Organization of nodes in edge computing
The tiers shown in Figure 2 are essentially a conceptual model (containing physical elements) and are
illustrative rather than definitive – in reality, the number of tiers and the type of node in each tier and the
networks connecting them are variable, depending on the nature of the system involved. There are multiple
tiers, containing varying types of nodes, all connected by networks which can also vary in nature depending
on the tiers involved.
Nodes in the device tier (i.e. the physical world points of attachment) are at or near the edge. They typically
contain lightweight nodes which commonly contain sensors or actuators or edge computing user (ECU)
interface devices (end-user node). Such devices often have limited compute and storage capabilities. The
networks used by this tier are often proximity networks, with limited bandwidth and limited range (see
[14]
6.1.2 and ISO/IEC 30141:2024 , 10.2.3.2 and 10.4.1.2).
Nodes in the edge tier are deployed near to devices in the device tier (where "near" is a relative term and
depends on the particular system and use case). Edge nodes can take on multiple roles:
— provide direct support to one or more nodes in the device tier;
— participate in edge peer networks (often called a mesh network) and serve as gateways to nodes in the
central tier; and
— provide support for one or more nodes in the central tier.
© ISO/IEC 2025 – All rights reserved
One type of node in the edge tier is the gateway node, for which an IoT gateway is one example. The role
of the gateway node is to interconnect proximity networks to communication networks. This often
involves message and protocol syntax and semantic conversions. This role includes message encryption,
deduplication and backup functions.
Another type of node in the edge tier is the control node. The control node receives data from nodes in
the device tier – typically data from sensors or input from ECU interface devices – and responds by issuing
instructions to other nodes in the device tier. Other types of nodes are placed in the edge tier to meet other
edge computing functional requirements. This includes management nodes, security nodes and software
support nodes.
Control nodes are usually placed in the edge tier due to issues of latency and timing. The response of a control
node is often time constrained (sometimes called real time, see Clause 14), such that the response is given
before some deadline following the receipt of some data or an event. One factor in this time constraint is the
transmission time of messages to and from nodes in the device tier – this leads to the need for the nodes in
the edge tier to be placed physically close to the device tier nodes and to the need to reduce the number of
hops that the messages take. These constraints can also influence the type of proximity network used and
the protocol used over those networks. Similarly, the control nodes have appropriate processing capacity
and storage for the processing that is necessary to produce appropriate and timely responses.
EXAMPLE If the input data is a video stream from a camera device, which is a type of sensor, and the processing
required is an analysis of the video to detect the movement of some object with the intent of influencing the movement
via some actuators (which are different devices from the camera), this takes a substantial amount of processing power
and also requires the handling of a substantial amount of data – the control node has appropriate processing power
and storage to successfully carry out its task.
The central tier represents a tier of nodes provided by centralized facilities. The nodes in the central tier
offer the ability to provide very substantial compute power and storage. The central tier is an excellent place
to conduct analytics or other processing that requires both a lot of compute power and access to a lot of
information. The central tier ca
...
ISO/IEC JTC 1/SC 38
Secretariat: ANSI
Date: 2025-04-2811-07
Information technology — Cloud computing — Edge computing
landscape
Technologies de l'information — Informatique en nuage — Environnement de l'edge computing
FDIS stage
© ISO/IEC 2025
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication
may be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying,
or posting on the internet or an intranet, without prior written permission. Permission can be requested from either ISO
at the address below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: + 41 22 749 01 11
E-mail: copyright@iso.org
Website: www.iso.org
Published in Switzerland
© ISO/IEC 2025 – All rights reserved
ii
Contents
Foreword . v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Edge computing . 2
3.2 IoT terms . 3
3.3 Real time . 4
3.4 Cloud computing . 5
4 Symbols and abbreviated terms . 5
5 Overview of edge computing . 6
5.1 General . 6
5.2 Concepts of edge computing . 7
5.3 Architectural foundations of edge computing . 9
5.4 Relationship of edge computing to cloud computing . 12
5.5 Relationship of edge computing to IoT . 17
6 Networking and edge computing . 19
6.1 General . 19
6.2 Virtual networks . 20
7 Hardware considerations for edge solution . 21
7.1 General . 21
7.2 Hardware capabilities . 21
8 Software technologies for edge solution . 23
8.1 General . 23
8.2 Software classifications . 23
8.3 Significant software technologies . 24
9 Deployment models and service capabilities types and service categories for edge
computing . 26
9.1 General . 26
9.2 Deployment models . 26
9.3 Service capabilities types . 27
9.4 Service categories . 27
10 Data in edge computing . 27
10.1 General . 27
10.2 Data flow . 28
10.3 Data storage . 30
10.4 Data processing . 31
11 Management of edge computing systems . 32
11.1 Management and orchestration fundamentals. 32
11.2 Management plane, control plane and data plane . 34
11.3 Cloud-based management and control of edge tier nodes and device tier devices . 37
11.4 Orchestration and maintenance . 38
11.5 Management of data, rights and resources . 38
11.6 Security and privacy management . 38
© ISO/IEC 2025 – All rights reserved
iii
12 Virtual placement . 38
13 Security and privacy in edge computing . 40
13.1 General . 40
13.2 Applying foundational security principles . 40
13.3 Secure nodes and devices . 41
13.4 Connectivity and network security . 42
13.5 Organization of security elements . 42
13.6 Privacy and personally identifiable information in edge computing . 45
14 Real time in edge computing . 46
14.1 General . 46
14.2 Factors influencing real time system design . 47
14.3 Design approaches for real time edge computing . 50
15 Edge computing and mobile devices . 51
Bibliography . 53
© ISO/IEC 2025 – All rights reserved
iv
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are members
of ISO or IEC participate in the development of International Standards through technical committees
established by the respective organization to deal with particular fields of technical activity. ISO and IEC
technical committees collaborate in fields of mutual interest. Other international organizations, governmental
and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types of
document should be noted. This document was drafted in accordance with the editorial rules of the ISO/IEC
Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the use of
(a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any claimed
patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had not received
notice of (a) patent(s) which may be required to implement this document. However, implementers are
cautioned that this may not represent the latest information, which may be obtained from the patent database
available at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held responsible for
identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/iso/foreword.html.
In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology,
Subcommittee SC 38, Cloud computing and distributed platforms.
This second edition cancels and replaces the first edition (ISO/IEC 23188:2020), which has been technically
revised.
The main changes are as follows:
— this document has been aligned with the ISO/IEC 22123 series;
Note 1 to entry: Any reference to “ISO/IEC 22123 series” refers to Part 1 as well as to Parts 2 and 3 of ISO/IEC 22123.
— reference to ISO/IEC 17788 and ISO/IEC 17789 have been changed to the ISO/IEC 22123 series;
— verbal forms have been updated in line with the ISO/IEC Directives Part 2.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html and www.iec.ch/national-
committees.
© ISO/IEC 2025 – All rights reserved
v
Introduction
Edge computing is increasingly used in systems that deal with aspects of the physical world. Edge computing
involves the placement of processing and storage near or at the points where those systems interact with the
physical world, which is where the "edge" exists. One of the trends is the development of increasingly capable
Internet of Things (IoT) devices (sensors and actuators), which generate more data or new types of data. There
is significant benefit from moving the processing and storing of this data closer to where the data is generated.
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities, i.e.
between the digital system and the physical world, delineated by networked sensors and actuators.
Pertinent digital entities mean that the digital entities which need to be considered can vary depending on the
system under consideration and the context in which those entities are used.
Modern systems such as those for IoT and OT applications include both cloud services and edge services. . This
can include the connection of both end-user devices and edge computing nodes to centralized cloud services.
It is also the case that cloud service provision is increasingly distributed. Cloud services are being
implemented in nodes that are closer to the end user in order to support reduced latency or to avoid
transferring large volumes of data over expensive networks. .
This document aims to describe edge computing and the significant elements which contribute to the
successful implementation of edge computing systems, with an emphasis on the use of cloud computing and
cloud computing technologies in the context of edge computing, including the virtualization of compute,
storage and networking resources.
[]
It is useful to read thisThis document is intended to be used in conjunction with ISO/IEC TR 30164, , which
takes a view of edge computing from the point of view of IoT systems and the IoT devices which interact with
the physical world.
© ISO/IEC 2025 – All rights reserved
vi
Information technology — Cloud computing — Edge computing
landscape
1 Scope
This document examines the concept of edge computing, its relationship to cloud computing and IoT, and the
technologies that are key to the implementation of edge computing. This document explores the following
topics with respect to edge computing:
— concept of edge computing systems;
— architectural foundation of edge computing;
— edge computing terminology;
— software classifications in edge computing, e.g. firmware, services, applications;
— supporting technologies, e.g. containers, serverless computing, microservices;
— networking for edge computing systems, including virtual networks;
— data, e.g. data flow, data storage, data processing;
— management, of software, of data and of networks, resources, quality of service;
— virtual placement of software and data, and metadata;
— security and privacy;
— real time operation;
— mobile edge computing, mobile devices.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 22123-1, Information technology — Cloud computing — Part 1: Vocabulary
ISO/IEC TS 23167, Information technology — Cloud computing — Common technologies and techniques
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 22123-1, ISO/IEC TS 23167 and
the following apply.
ISO and IEC maintain terminologicalterminology databases for use in standardization at the following
addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp
— IEC Electropedia: available at https://www.electropedia.org/
© ISO/IEC 2025 – All rights reserved
3.1 Edge computing
3.1.1
distributed computing
model of computing in which a set of nodes (3.1.9(3.1.9)) coordinates its activities by means of digital
messages passed between the nodes
3.1.2
edge
boundary between pertinent digitalentities (3.2.2digital entities (3.2.2)) and physical entities (3.2.8),
delineated by sensors (3.2.9()) and actuators (3.2.1)
Note 1 to entry: Pertinent digital entities means that the digital entities which need to be considered can vary depending
on the system under consideration and the context in which those entities are used.
Note 2 to entry: Pertinent physical entities can include devices other than sensors and actuators.
Note 3 to entry: The edge can be placed at the edge end or the device end of the proximity network connecting them,
often depending on who owns or operates the proximity network.
3.1.3
edge computing
distributed computing (3.1.1) in which some or all processing and storage takes place at or near the edge
(3.1.2), where the nearness is defined by the system's requirements
3.1.4
edge computing service
one or more capabilities offered via edge computing (3.1.3) invoked using a defined interface
3.1.5
edge computing system
system providing functionalities of edge computing (3.1.3)
Note 1 to entry: Edge computing systems to include capabilities for both edge computing and cloud computing
3.1.6
edge computing user
ECU
user of edge computing system (3.1.5(3.1.5))
3.1.7
edge solution
edge computing services (3.1.4(3.1.4)) combined and controlled to meet edge computing user‘s (3.1.6(3.1.6))
requirements.
3.1.8
endpoint
entity (3.2.4(3.2.4)) that exposes and uses one or more network interfaces.
Note 1 to entry: An endpoint includes any hardware device that is capable of sending or receiving data over a network.
[SOURCE: ISO/IEC 20924:2024, 3.1.15, modified –— In the definition, "component" has been replaced by
"entity" to broaden the scope.]
3.1.9
node
networked machine with processing and storage capabilities
© ISO/IEC 2025 – All rights reserved
Note 1 to entry: Both digital and physical entities are examples of nodes. Virtual machine or container in cloud solution
would also be a node.
3.1.10
operational technology
OT
hardware and software that detects or causes a change through the direct monitoring and/or control of
physical devices and systems, processes and events in the organization
3.2 IoT terms
3.2.1
actuator
IoT device (3.2.5(3.2.6)) that changes one or more properties of a physical entity (3.2.8) in response to an input
[SOURCE: ISO/IEC 20924:2024, 3.2.2]
3.2.2
actuating
changing one or more properties of a physical entity in response to an input
[SOURCE: IIC vocabulary v3,0]
3.2.3
digital entity
entity (3.2.3 (3.2.3)) that exists in the digital realm
Note 1 to entry: A digital entity can exist in several forms, including a cloud service (3.4.2 (3.4.2)) or X as a service in a
data centre, or as a network element or as an IoT gateway (3.2.6 (3.2.7).).
[SOURCE: ISO/IEC 20924:2024, 3.1.13]
3.2.43.2.3
entity
anything (physical or non-physical) having a distinct existence
[SOURCE: ISO/IEC 15459-3:2014, 3.1]
3.2.53.2.4
Internet of Things
IoT
infrastructure of interconnected entities, people, systems and information resources together with services
which processes and reacts to information from the physical world and virtual world
[SOURCE: ISO/IEC 20924:2024, 3.2.8]
3.2.63.2.5
IoT device
endpoint (3.1.8(3.1.8)) that interacts with the physical world through sensing or actuating
Note 1 to entry: An IoT device (3.2.5)) can be a sensor (3.2.9(3.2.11)) or an actuator (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.11]
© ISO/IEC 2025 – All rights reserved
3.2.73.2.6
IoT gateway
entity of an IoT system (3.2.7(3.2.8)) that connects one or more proximity networks and the IoT devices (3.2.5))
on those networks to each other and to one or more access networks
[SOURCE: ISO/IEC 20924:2024, 3.2.14]
3.2.83.2.7
IoT system
system providing functionalities of Internet of Things (3.2.4))
Note 1 to entry: IoT system is inclusive of IoT devices (3.2.5(3.2.6),), IoT gateways (3.2.6(3.2.7),), sensors (3.2.9(3.2.11),),
and actuators (3.2.1).
[SOURCE: ISO/IEC 20924:2024, 3.2.15]
3.2.93.2.8
physical entity
entity in the physical world that can be the subject of sensing (3.2.10) and/or actuating (3.2.2)
[SOURCE: ISO/IEC 20924:2024, 3.1.25]
3.2.103.2.9
sensing
observing one or more properties of a physical entity () and converting those properties into information
[SOURCE: ISO/IEC 20924:2024, 3.2.19]
3.2.11
sensor
IoT device (3.2.5(3.2.6) )with the capability of sensing(3.2.10)
[SOURCE: ISO/IEC 20924:2024, 3.2.20]
3.3 Real time
3.3.1
real time
processing of data by a computer in connection with another process outside the computer according to time
requirements imposed by the outside process
[SOURCE: ISO/IEC 2382:2015, 2122900, modified — words 'pertaining to'"pertaining to" has been removed
to improve substitutability of definition; Notes 1 to 3 to entry have been removed.]
3.3.2
real time system
system in which processing meets real time (3.3.1) requirements
3.3.3
hard real time
real time system (3.3.2) whose operation is incorrect if results are not produced according to specified timing
requirements
3.3.4
soft real time
real time system (3.3.2) whose operation is degraded if results are not produced according to specified timing
requirements
© ISO/IEC 2025 – All rights reserved
3.4 Cloud computing
3.4.1
cloud computing
paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources
with self-service provisioning and administration on demand
[SOURCE: ISO/IEC 22123-1:2023, 3.1.1, modified –— Notes 1 and 2 to entry have been deleted.]
3.4.2
cloud service
one or more capabilities offered via cloud computing (3.4.1 (3.4.1)) invoked using a defined interface
4 Symbols and abbreviated terms
AC Alternating current
BYOD Bring Your Own Device
CDN Content Distribution Network
CPU Central Processing Unit
CSC Cloud service customer
CSP Cloud service provider
CSU Cloud service user
DDoS Distributed Denial of Service
DevSecOps Development, Security, and Operations
ECU Edge computing user
EPG Electronic Programme Guide
EPROM Erasable Programmable Read Only Memory
FPGA Field Programmable Gate Array
FPS Frame Per Second
Gb Gigabyte
GPS Global Positioning System
GPU Graphics Processing UnitIdentity
ID
ID Identity
IETF Internet Engineering Task Force
IoT Internet of Things
IP Internet Protocol
IPTV Internet Protocol television
LAN Local Area Network
MDM Mobile Device Management
OS Operating system
OS Operating systemOperations Support System
© ISO/IEC 2025 – All rights reserved
OSS
PC Personal Computer
PII Personally Identifiable Information
RAM Random-access Memory
RFC Request for Comments
ROM Read Only Memory
ROM Read Only MemorySubscriber Identity Module
SIM
TPM Trusted Platform Module
VM Virtual Machine
VoIP Voice over Internet Protocol
VPN Virtual Private Network
WiFi Wireless Fidelity
5 Overview of edge computing
5.1 General
Over time, the forms of computing have varied between centralized and distributed, depending on the nature
and capabilities of the computing devices and of the networks used to connect them.
Mainframe computers represent a form of centralised computing, where the main computer systems are
placed in a data centre, containing processing and storage units. Originally, almost the whole of the computing
system was situated within the data centre. Gradually, time-sharing terminals were located in remote
locations to provide user access to the mainframe systems. Terminals were typically little more than a display
with a keyboard for input and the associated network connection had limited bandwidth, perhaps involving a
dial-up modem.
The personal computer (PC) represents a distributed form of computing. The PC has significant processing
and storage capabilities and can be used very effectively in a standalone mode. However, PCs are more
typically used in a networked mode. Initially, the networks were used for simple communications such as (text
based) email, but as the network bandwidth increased over time, increasingly sophisticated activities took
place, with file transfer and eventually peer-to-peer capabilities being used.
The availability of higher bandwidth networking encouraged the development of the client-server
architecture, with the PC used for the clients, connected to a centralized server which performs the main
processing and storage. Clients can include quite substantial software elements performing significant
processing activities. Data mightcan also be stored locally for faster access, although the main database(s) are
held centrally.
The advent of the internet and the World Wide Web (WWW) represents the appearance of another form of
computing. In this form of computing, web servers serve up web pages and related material which are
accessed through client’s web browsers. Devices running web browsers can be relatively low in compute
power, while the web servers for some of the more popular and high demand web sites can involve massive
compute power spread over many machines in a large data centre.
Cloud computing is a computing paradigm that provides various types of computing resources on demand in
a highly scalable manner through cloud computing services. In practice, it relies on a highly centralized
architecture, with computing resources concentrated in large data centres. However, cloud computing also
© ISO/IEC 2025 – All rights reserved
incorporates certain features of distributed computing. It is common for cloud service providers to operate
multiple physically separated data centres, and cloud service users (CSUs) often use applications and data to
be distributed across these centres using cloud computing service – for resilience, to reduce latency and for
disaster recovery purposes. In addition, the favoured design paradigm for cloud native applications is to
distribute multiple instances of each application component across different machines within the cloud
computing system. This design paradigm and the technologies that support it are of significance to edge
computing.
5.2 Concepts of edge computing
Edge computing is distributed computing in which data processing and storage takes place on nodes which
are near to the edge. The edge is marked by the boundary between pertinent digital and physical entities, i.e.
between the digital system and the physical world, delineated by networked sensors and actuators. The
concept of edge computing is shown in Figure 1.
© ISO/IEC 2025 – All rights reserved
Figure 1 — Concept of edge computing
Pertinent digital entities mean that the digital entities which need to be considered can vary depending on the
system under consideration and the context in which those entities are used.
An example of varying pertinence are the servers within a cloud computing data centre. When cloud service
customers (CSCs) use cloud services deployed on such servers to build IoT systems, it is difficult to say that
the location of IoT sensors is always at the edge. However, from the perspective of the cloud service providers
© ISO/IEC 2025 – All rights reserved
(CSPs) having to manage the cloud computing data centre, it is highly likely that the servers are instrumented
with a variety of sensors capable of reporting various physical properties of the servers, for example their
temperature. Those sensors are at the edge.
Nearness for edge computing is usually based on minimising the latency for communication between the IoT
devices that are at the edge and the place(s) where data processing and storage occurs. Nearness can mean
placing the edge computing nodes physically close to the IoT devices or near the communication network
nodes connect the IoT devices to data centres or the places where data processing and storage occurs. In the
most extreme cases, nearness means combining the sensors and actuators and edge computing into a single
node, as mightwill possibly happen with a smart phone. In other cases, the edge computing nodes are
separated from the IoT devices but are placed physically close to the IoT devices and have a proximity network
connecting them or close to communication network nodes connected IoT devices to minimise latency.
Nearness can also be influenced by the nature of the networks and the volume of data flowing to and from the
IoT devices – where large volumes of data and high data rates are involved, edge nodes are placed so as to
reduce the latency of handling this data to the minimum necessary to meet the requirements of the use case.
Digital systems can observe and affect the physical world. Sensors and actuators are at the edge between the
digital systems and the physical world. Edge computing systems generally combine these IoT devices with
distributed computing resources to provide the capabilities of the system. In edge computing systems, actions
often need to occur within specific timeframes, i.e. edge computing systems can also be real time systems, and
latency considerations affect system design and the choice of the placement of data processing and storage to
achieve timing requirements. Edge computing helps to meet those timing requirements.
Edge computing is characterized by networked systems in which significant data processing and storage takes
place on nodes near the edge, rather than in some centralized location. Edge computing can be contrasted with
centralized computing where the centralized nodes are remote from the edge. However, it is important to note
that edge computing is complementary to centralized forms of computing and that in any given system, edge
computing is often used in conjunction with centralized computing.
There are multiple reasons for the rise in the use of edge computing. One reason is the arrival of new devices
combining significant processing power and storage with low power usage. Smart phones have been one of
the driving factors in this area, with billions of such devices in daily use. The Internet of Things (IoT) is another
reason, with small, low power, low cost IoT devices enabling the creation of IT systems which can sense and
act on real world entities.
5.3 Architectural foundations of edge computing
Edge computing involves nodes that are commonly arranged in tiers of compute and storage capabilities. They
can be highly heterogeneous both within a tier and across different tiers. A simplified view of the organization
of edge computing nodes and the networks connecting them in edge computing is shown in Figure 2.
© ISO/IEC 2025 – All rights reserved
Figure 2 — Organization of nodes in edge computing
The tiers shown in Figure 2 are essentially a conceptual model (containing physical elements) and are
illustrative rather than definitive – in reality, the number of tiers and the type of node in each tier and the
networks connecting them are variable, depending on the nature of the system involved. What is important to
understand is that thereThere are multiple tiers, containing varying types of nodes, all connected by networks
which can also vary in nature depending on the tiers involved.
Nodes in the device tier (i.e.,. the physical world points of attachment) are at or near the edge. They typically
contain lightweight nodes which commonly contain sensors or actuators or edge computing user (ECU)
interface devices. (end-user node). Such devices often have limited compute and storage capabilities. The
networks used by this tier are often proximity networks, with limited bandwidth and limited range (see 6.1.2
[ ] []
and ISO/IEC 30141:2024 14see clauses , 10.2.3.2 and 10.4.1.2 in ISO/IEC 30141:2024, ).).
Nodes in the edge tier are deployed near to devices in the device tier (where "near" is a relative term and
depends on the particular system and use case). Edge nodes can take on multiple roles:
© ISO/IEC 2025 – All rights reserved
— provide direct support to one or more nodes in the device tier;
— participate in edge peer networks (often called a mesh network) and serve as gateways to nodes in the
central tier; and
— provide support for one or more nodes in the central tier.
One type of node in the edge tier is the gateway node, for which an IoT gateway is one example. The role of the
gateway node is to interconnect proximity networks to communication networks. This often involves message
and protocol syntax and semantic conversions. This role includes message encryption, deduplication and
backup functions.
Another type of node in the edge tier is the control node. The control node receives data from nodes in the
device tier – typically data from sensors or input from userECU interface devices – and responds by issuing
instructions to other nodes in the device tier. Other types of nodes are placed in the edge tier to meet other
edge computing functional requirements. This includes management nodes, security nodes and software
support nodes.
Control nodes are usually placed in the edge tier due to issues of latency and timing. The response of a control
node is often time constrained (sometimes called real time –, see Clause 14), such that the response is given
before some deadline following the receipt of some data or an event. One factor in this time constraint is the
transmission time of messages to and from nodes in the device tier – this leads to the need for the nodes in the
edge tier to be placed physically close to the device tier nodes and to the need to reduce the number of hops
that the messages take. These constraints can also influence the type of proximity network used and the
protocol used over those networks. Similarly, the control nodes have appropriate processing capacity and
storage for the processing that is necessary to produce appropriate and timely responses.
As an example, ifEXAMPLE If the input data is a video stream from a camera device, which is a type of sensor, and
the processing required is an analysis of the video to detect the movement of some object with the intent of influencing
the movement via some actuators (which are different devices from the camera), this takes a substantial amount of
processing power and also requirerequires the handling of a substantial amount of data – the control node havehas
appropriate processing power and storage to successfully carry out its task.
The central tier represents a tier of nodes provided by centralized facilities. The nodes in the central tier offer
the ability to provide very substantial compute power and storage. The central tier is an excellent place to
conduct analytics or other processing that requires both a lot of compute power and access to a lot of
information. The central tier can hold large stores of information which can come from many sources – this
can be from across the other tiers or from outside locations, potentially sourced from other organizations. The
central tier can provide services to the other tiers, including services for processing data in various ways or
for holding information or providing information as required. The central tier usually has a wide span of
connectivity, meaning that it is commonly connected to many other systems, including many of the distributed
nodes in both the edge tier and in the device tier.
It is often the case that the central tier is implemented using cloud computing. A fuller description of the
relationship of edge computing to cloud computing is given in 5.4.
It is typical of the nodes in the central tier to communicate to the other tiers using high bandwidth networks,
typically the internet but possibly dedicated networks. It is also possible for the nodes in the central tier to be
arranged in a highly available resilient configuration, with multiple instances of applications and services
allied to replicated or redundant copies of information.
The tiers described in Figure 2 can become blurred when considering the many different types of devices that
are available. A significant example is the smartphone, which combines a number of elements into a single
device, as follows:
© ISO/IEC 2025 – All rights reserved
— sensors of various types, including GPS (location sensor), accelerometer, barometer, health monitors (such
as heart rate monitoring);
— camera – both for static images and video;
— microphone &and loudspeaker for audio;
— display screen and user interface;
— significant compute power;
— significant local storage;
— networking and connectivity.
These capabilities in a single device span the device tier and the edge tier and provide for dynamic addition
and update of software on the device, enabling a very wide range of capabilities. Combined with excellent
networking capabilities, smartphones enable some forms of edge computing in their own right – with the
added advantage of their being mobile.
5.4 Relationship of edge computing to cloud computing
Edge computing can exist on its own, without any relationship to cloud computing. In terms of the tiers
described in 5.3, systems can exist in which cloud computing is not used in any of the tiers. This implies that
the system has no need of services offered by cloud computing. Older industrial systems are of this nature –
designed to be self-contained and with fixed functionality.
However, cloud computing service or cloud computing technologies are used in one or more of the tiers. This
is especially so for the central tier – it is very common for the nodes in the central tier to be part of a cloud
computing, either a public cloud or a private cloud. The emergence of small-scale, high-performance hardware
and cloud-native software techniques enables cloud computing services to be deployed in the edge tier.
Although today use of cloud computing in the device tier is unusual and rare, there is nothing in principle to
preclude its use once the device nodes are sufficiently powerful and well-connected.
It is worth noting that edgeEdge computing rarely exists on its own, but is connected to both processing and
information which is held in the central tier. This means systems have processing and storage spread right
across the various tiers and types of nodes. The principle is the right placement of processing and storage
elements. Right placement in that processing and storage take place on nodes that are best suited to the task
involved.
Figure 3 illustrates how IoT devices and edge computing can relate to different parts of the cloud computing
ecosystem. This can include cloud services built on a private cloud (both on-premises and more remotely) and
a public cloud (including public clouds designed to serve a specific jurisdiction, or multinational or even global
cloud services). Hybrid clouds of various kinds can also be employed according to business needs, as in the
example shown in Figure 3 where a public cloud in the central tier is combined with a private cloud in the
edge tier.
© ISO/IEC 2025 – All rights reserved
Figure 3 — Relationship of edge computing to cloud computing
The central tier can provide public cloud services, and these public cloud services can use either a
multinational public cloud (i.e. multiple data centres in a number of jurisdictions) or a national public cloud
(for example,e.g. where there are restrictions on where the data can be stored and processed). The central tier
can also use an enterprise-wide private cloud.
© ISO/IEC 2025 – All rights reserved
The edge tier can use an on-premises private cloud, physically located to suit the needs of the edge computing
service. However, it is the case that some public clouds make available cloud services on a more physically
localised basis, potentially suitable for edge computing systems.
EXAMPLE 1 A prime example of a more physically localized cloud service offering is the computing capabilities of
cellular telephone towers. Such distributed public cloud offerings are used for the edge tier. As an example, in this latter
case, the device tier nodes are directly connected using mobile phone networks to nodes running in cellular telephone
towers.
In order to reduce latency and achieve timing goals, it is possible to place control processing on edge tier
nodes, where those nodes are physically close to the device tier such as a co-located on-premises private cloud.
However, for processing that involves analysis of large volumes of data that arise from many different sources,
it is likely that centralized storage is the best approach, allied to the substantial processing power available
for analytics software in the central tier using public cloud services. For any given system, it is likely that both
types of processing are required and need to be combined effectively.
EXAMPLE 2
For example, direct Direct control of a manufacturing production line is likely to be placed in the edge tier
– particularly where real time responses are required to the arrival of data and events. However, the overall goals of the
production line such as the product mix to produce, are much more likely to be decided by applications and services in
the central tier, which are analysing a lot of external data, combined with information about business goals. Such goals
are then passed down from the central tier to the edge tier for implementation.
© ISO/IEC 2025 – All rights reserved
Key
indicates associated tier for a component
API invocation
indicates associated tier for a component
API invocation
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Figure 4 — Relationship of edge computing tiers to cloud computing
Figure 4 aims to show the relationship of edge computing to cloud computing as described in ISO/IEC 22123-
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3 9. It is ne
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