ETSI TR 103 195-1 V1.1.1 (2023-09)

Core Network and Interoperability Testing (INT/ WG AFI) Generic Autonomic Network Architecture; Part 1: Business drivers for autonomic networking

DTR/INT-002-1_AFI-0015-1-GS02

General Information

• Status: Not Published
• Technical Committee: INT AFI - Evolution of Management towards Autonomic Future Internet
• Current Stage: 12 - Completion
• Due Date: 19-Sep-2023
• Completion Date: 08-Sep-2023

Standards Content (Sample)

TECHNICAL REPORT
Core Network and Interoperability Testing (INT/ WG AFI)
Generic Autonomic Network Architecture;
Part 1: Business drivers for autonomic networking

2 ETSI TR 103 195-1 V1.1.1 (2023-09)

Reference
DTR/INT-002-1_AFI-0015-1-GS02
Keywords
autonomic networking, self-management
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3 ETSI TR 103 195-1 V1.1.1 (2023-09)
Contents
Intellectual Property Rights . 4
Foreword . 4
Modal verbs terminology . 4
1 Scope . 5
2 References . 5
2.1 Normative references . 5
2.2 Informative references . 5
3 Definition of terms, symbols and abbreviations . 6
3.1 Terms . 6
3.2 Symbols . 6
3.3 Abbreviations . 6
4 Business Value of Autonomics for Management and Control of Networks and Services . 7
4.1 Definition of the Autonomic Management & Control paradigm. 7
4.1.1 Autonomic Management & Control . 7
4.1.2 Automated Management . 8
4.1.3 Autonomic Management & Control vs Automated Management. 8
4.2 A Combined View on Business drivers for AMC, SDN and NFV . 9
4.3 How a cross-SDO combined approach on AMC, SDN and NFV helps achieve operators' business
objectives . 10
4.4 Revenue Generation using a combination of AMC, SDN, NFV, E2E Service Orchestration and Big-
Data Analytics in Network Provider Environments . 11
4.5 Enablers for Live Cycle Management and Operationalization of Autonomics in Network Architectures
Management and Control Planes . 12
5 Business Models of GANA . 12
5.1 The Business Value of the GANA Knowledge Plane . 12
5.2 The Stakeholders to whom the GANA Model Addressed: A Perspective on Business Models and
Opportunities Enabled by the GANA . 13
5.3 Business Governance - Profiles and Policies. 15
History . 17

ETSI
4 ETSI TR 103 195-1 V1.1.1 (2023-09)
Intellectual Property Rights
Essential patents
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pertaining to these essential IPRs, if any, are publicly available for ETSI members and non-members, and can be
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Foreword
This Technical Report (TR) has been produced by ETSI Technical Committee Core Network and Interoperability
Testing (INT).
The present document is part 1 of a multi-part deliverable covering the Generic Autonomic Network Architecture, as
identified below:
ETSI TR 103 195-1: "Business drivers for autonomic networking";
ETSI TS 103 195-2: "An Architectural Reference Model for Autonomic Networking, Cognitive Networking
and Self-Management";
ETSI TR 103 195-3: "Guidelines for instantiation and implementation".
Modal verbs terminology
In the present document "should", "should not", "may", "need not", "will", "will not", "can" and "cannot" are to be
interpreted as described in clause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of provisions).
"must" and "must not" are NOT allowed in ETSI deliverables except when used in direct citation.

ETSI
5 ETSI TR 103 195-1 V1.1.1 (2023-09)
1 Scope
The scope of the present document is to identify key actors and related roles and responsibility demarcation within
autonomic, cognitive and self-managed network ecosystem. Business drivers behind this Autonomic Management &
Control (AMC) ecosystem as described through Generic Autonomic Network architecture (GANA) framework is at the
heart of the present document. Monetary value creations in terms of measurable metrics (e.g. OPEX) that reflect cost
benefit brought by the use of autonomics.
2 References
2.1 Normative references
Normative references are not applicable in the present document.
2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee
their long term validity.
The following referenced documents are not necessary for the application of the present document but they assist the
user with regard to a particular subject area.
[i.1] Ranganai Chaparadza: "Requirements for a Generic Autonomic Network Architecture (GANA),
suitable for Standardizable Autonomic Behaviour Specifications for Diverse Networking
Environments". International Engineering Consortium (IEC), Annual Review of Communications,
61, 2008.
[i.2] ETSI White Paper No. 16 (First edition - October 2016): "GANA - Generic Autonomic
Networking Architecture - Reference Model for Autonomic Networking, Cognitive Networking
and Self-Management of Networks and Services". ISBN No. 979-10-92620-10-8.
[i.3] ETSI GS AFI 002: "Autonomic network engineering for the self-managing Future Internet (AFI);
Generic Autonomic Network Architecture (An Architectural Reference Model for Autonomic
Networking, Cognitive Networking and Self-Management)".
[i.4] R. Chaparadza, Tayeb Ben Meriem, Benoit Radier, Szymon Szott, Michal Wodczak, Arun
Prakash, Jianguo Ding, Said Soulhi, Andrej Mihailovic: "SDN Enablers in the ETSI AFI GANA
Reference Model for Autonomic Management & Control (emerging standard), and Virtualization
Impact". In the proceedings of the 5th IEEETM MENS Workshop at IEEE Globecom 2013,
December, Atlanta, Georgia, USA.
[i.5] R. Chaparadza, Tayeb Ben Meriem, Benoit Radier, Szymon Szott, Michal Wodczak, Arun
Prakash, Jianguo Ding, Said Soulhi, Andrej Mihailovic: "Implementation Guide for the ETSI AFI
GANA Model: a Standardized Reference Model for Autonomic Networking, Cognitive
Networking and Self-Management". In the proceedings of the 5th IEEETM MENS Workshop at
IEEE Globecom 2013, December, Atlanta, Georgia, USA.
[i.6] Accepted PoC proposals.
[i.7] TMForum: "Promoting a trusted telco data space to drive new opportunities".
[i.8] ETSI TS 103 195-2 (V1.1.1): "Autonomic network engineering for the self-managing Future
Internet (AFI); Generic Autonomic Network Architecture; Part 2: An Architectural Reference
Model for Autonomic Networking, Cognitive Networking and Self-Management".
ETSI
6 ETSI TR 103 195-1 V1.1.1 (2023-09)
[i.9] ETSI GANA White Paper N 1: "C-SON Evolution for 5G, Hybrid SON Mappings to the ETSI
GANA Model, and achieving E2E Autonomic (Closed-Loop) Service Assurance for 5G Network
Slices by Cross-Domain Federated GANA Knowledge Planes".
[i.10] ETSI TR 103 195-3: "Core Network and Interoperability Testing (INT/ WG AFI); Generic
Autonomic Network Architecture; Part 3: Guidelines for instantiation and implementation".
[i.11] ETSI TS 103 194: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Scenarios, Use Cases and Requirements for Autonomic/Self-
Managing Future Internet".
[i.12] ETSI TR 103 473 (V1.1.2): "Evolution of management towards Autonomic Future Internet (AFI);
Autonomicity and Self-Management in the Broadband Forum (BBF) Architectures".
[i.13] ETSI TR 103 404: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Autonomicity and Self-Management in the Backhaul and
Core network parts of the 3GPP Architecture".
[i.14] ETSI TR 103 495: "Network Technologies (NTECH); Autonomic network engineering for the
self-managing Future Internet (AFI); Autonomicity and Self-Management in Wireless
Ad-hoc/Mesh Networks: Autonomicity-enabled Ad-hoc and Mesh Network Architectures".
[i.15] ETSI TR 103 747: "Core Network and Interoperability Testing (INT/ WG AFI); Federated GANA
Knowledge Planes (KPs) for Multi-Domain Autonomic Management & Control (AMC) of Slices
in the NGMN(R) 5G End-to-End Architecture Framework".
[i.16] ETSI TR 103 627: "Core Network and Interoperability Testing (INT/WG AFI) Autonomicity and
Self-Management in IMS architecture".
3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the terms given in ETSI TS 103 195-2 [i.8] apply.
3.2 Symbols
For the purposes of the present document, the symbols given in ETSI TS 103 195-2 [i.8] apply.
3.3 Abbreviations
For the purposes of the present document, the abbreviations given in ETSI TS 103 195-2 [i.8] and the following apply:
rd
3GPP 3 Generation Partnership Project
AI Artificial Intelligence components
AMC Autonomic Management and Control
BBF BroadBand Forum
BSS Business Support System
CAPEX CAPital EXpenditure
CHOP Configuration Healing Optimization Protection
NOTE: In autonomics, Self-CHOP refers to these Self-* features: Self-Configuration, Self-Healing,
Self-Protection, etc.
CPE Customer Premises Equipment
CSP Communication Service Provider
DE Decision making Element
FB Functional Block
GANA Generic Autonomic Network Architecture
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7 ETSI TR 103 195-1 V1.1.1 (2023-09)
IEEE Institute of Electrical and Electronics Engineers
ISV Independent Software Vendor
KPI Key Performance Indicators
ME Managed Entity
NE Network Element
NFV Network Functions Virtualization
NGMN Next Generation Mobile Network
OPEX OPerational Expenditure
OSS Operations Support System
PoC Proof of Concept
QoE Quality of Experience
QoS Quality of Service
SDN Software-Defined Networking
SDO Standardization Development Organization
SLA Service Level Agreement
USP Unique Selling Point
4 Business Value of Autonomics for Management and
Control of Networks and Services
4.1 Definition of the Autonomic Management &
Control paradigm
4.1.1 Autonomic Management & Control
Autonomic networks enable product innovation, network services innovation, operational efficiency for networks and
services and smart and intelligent networks that exhibit self-* features such as self-configuration, self-repair/healing,
self-protection, self-optimization, and self-awareness. The industry consensus is that as networks evolve, networks and
services need to be operated based on principles for dynamically adaptive "automated" and "autonomic" management &
control.
Autonomic Management & Control (AMC) is about Decision-making-Elements (DEs) as autonomic functions
(i.e. control-loops) with optionally cognition introduced in the management plane as well as in the control plane
(whether these planes are distributed or centralized).
Cognition (learning, analysing, and reasoning used to effect advanced adaptation) in DEs, enhances DE logic and
enables DEs to manage and handle even the unforeseen situations and events detected in the environment around them.
Control is about control-logic as the kernel of the DE that uses a control-loop to dynamically adapt network resources
and parameters or services in response to changes in network goals/intent/policies, context and challenges in the
network environment that affect service availability, reliability, and quality.
DEs realize self-* features (self-configuration, self-optimization, etc.) as a result of the decision-making behaviour of a
DE that performs dynamic/adaptive management and control of its associated Managed Entities (MEs) and their
configurable and controllable parameters. Such a DE can be embedded in a Network Element (NE) or higher at a
specific layer of the outer overall network and services management and control architecture. An NE may be physical or
virtualised (such as in the case of the Network Function Virtualisation (NFV) paradigm).
From an architecture perspective, a control-loop can be based on a distributed model (for fast control-loops). In this
case the DE is embedded in the NE (physical or virtualised). Whereas in a centralized model (for slow control-loops),
the DE is embedded (implemented) outside of the NEs. Both kinds of control-loops act towards a global goal to ensure
a stable state of the network. A DE can negotiate with another DE to realize dynamic adaptation of network resources
and parameters, or services, via reference points.
This leads to the notion of global network autonomics, a result of interworking DEs as collaborative manager
components that perform AMC of their associated MEs within NEs and their parameters.
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8 ETSI TR 103 195-1 V1.1.1 (2023-09)
From an implementation perspective, a DE, as a software module or an executable behavioural specification that
enhances intelligence capabilities, may be (re)-loaded or replaced in NEs and in the network's centralized management
and control plane. This is directly related to the notion of software-driven networks or software-empowered networks.
DEs (software components) are meant to empower the networks and the management and control planes to realize
self-* properties: auto-discovery of information/resources/capabilities/services; self-configuration; self-protecting;
self-diagnosing; self-repair/healing; self-optimization; self-organization behaviours; as well as self-awareness.
AMC also includes the following aspects for dynamic, intelligent, and adaptive management and control of networks
and services (even when considering the emergence of SDN (Software-Defined Networking)):
• Real-time reactive and proactive network analytics that should be instrumented at various layers of the
management and control realms for networks. Network analytics involves strategies and techniques to gather
various data (e.g. monitoring data) and analyse the data, so as to infer changes in the state of network resources
and deduce any patterns that help build knowledge pertaining to network state transitions, event predictions,
and forecasts. The analysis process and the knowledge built is used to decide actions that can be performed to
achieve certain objectives.
• Dynamic network policing and dynamic service(s) policing.
• Self-* features such as self-organizing network behaviours, self-configuration; self-protection; self-diagnosis;
self-repair; self-healing; self-optimization; self-awareness.
• Autonomic services management (on-demand orchestration and dynamic adaptation/re-programming of
services).
• Network applications that provide for network intelligence by controlling the network via the northbound API
of a Software-Defined Networking SDN controller (e.g. a hybrid SDN controller-one that exhibits a
multi-protocol southbound interface to diverse virtual and physical networks).
• In-network management for aspects requiring in-network reaction and self-adaptation by a thinly instrumented
in-network control plane. The in-network control plane could be complemented by an outer and more complex
logically centralized control plane that is split from the data plane as in the case of SDN.
In a nutshell, AMC is the key to designing the network and management & control intelligence (software logic) that
enables the network and associated management and control operations to dynamically self-adapt to operator's high
level business goals/intents/objectives and policy changes, challenges to the network (i.e. manifestations of faults,
errors, failures, performance degradation) and workload conditions of operation. To achieve AMC, real-time and
predictive network analytics (also including predictive and proactive actions) for dynamic network policing and
services (re-) programmability as driven by changes in context, workload scenarios, security, and services requirements,
should be introduced in the network architecture designs and the resulting network infrastructures that get deployed.
4.1.2 Automated Management
Automated management is about workflow reduction and automation i.e. automation of the processes involved in the
creation of network configuration input using specialized task automation tools (e.g. scripts, network planning tools,
policy generators for conflict-free policies).
4.1.3 Autonomic Management & Control vs Automated Management
Autonomic management can be contrasted to automated management. The former emphasizes learning, reasoning, and
adaptation, while the latter focuses on efficient workflow implementation and automation of the processes involved in
the creation of network configuration and monitoring tasks. Figure 1 illustrates the positioning of both paradigms and
highlights the interaction between them.
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9 ETSI TR 103 195-1 V1.1.1 (2023-09)

Figure 1: Automated Management vs Autonomic Management illustration
(their interaction and complementarity)
Automated management provides input to the AMC. Indeed, autonomic management exhibit a network governance
interface through which the input that governs the configuration of an autonomic network should be provided. Thanks
to automation tools and mechanisms, by using a high-level language the operator can define the features of the network
services that should be provided by the underlying network infrastructure. Such a business language that can help the
operator express high level business goals required of the network may be modelled using an ontology to add semantics
and enable machine reasoning on the goals. The human operator defined features relate to business goals, technical
goals, and some input configuration data that an autonomic network is supposed to use for network resources and
parameter configuration.
4.2 A Combined View on Business drivers for AMC, SDN and
NFV
New Networks and associated Services are becoming increasingly complex to manage, resulting in excessive OPEX
consumption. Operators have two mains business drivers:
1) define a set of cost saving methods and technologies that have the potential to achieve substantial Operational
Expenditure (OPEX) savings;
2) introduce dynamicity in the Operations Support System (OSS) and Business Support System (BSS) to cope
with the lack of Services agility, provide better Customer experience, and reduce time-to-deploy and time-to-
market.
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10 ETSI TR 103 195-1 V1.1.1 (2023-09)
The above two business drivers mandate introducing flexibility and programmability into the network. This means that
management functions will be incorporated into all parts of the system, and not just confined to OSSs and BSSs. AMC
provides capabilities, such as knowledge dissemination and intelligent decision-making, to achieve these business
objectives. It can also be used to integrate different approaches, including Software-Defined Networkings (SDNs)
which could drive the networks, Network Functions Virtualization
...