ETSI GR F5G 019 V1.1.1 (2025-04)

Fifth Generation Fixed Network (F5G); Fixed Network Autonomous Network level definition and evaluation

DGR/F5G-0019

General Information

• Status: Not Published
• Technical Committee: F5G - Fifth Generation Fixed Network
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Due Date: 28-Apr-2025
• Completion Date: 04-Apr-2025

Standards Content (Sample)

GROUP REPORT
Fifth Generation Fixed Network (F5G);
Fixed Network Autonomous Network level definition and
evaluation
Disclaimer
The present document has been produced and approved by the Fifth Generation Fixed Network (F5G) ETSI Industry
Specification Group (ISG) and represents the views of those members who participated in this ISG.
It does not necessarily represent the views of the entire ETSI membership.

2 ETSI GR F5G 019 V1.1.1 (2025-04)

Reference
DGR/F5G-0019
Keywords
autonomous network, F5G, F5G advanced,
network management
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3 ETSI GR F5G 019 V1.1.1 (2025-04)
Contents
Intellectual Property Rights . 5
Foreword . 5
Modal verbs terminology . 5
1 Scope . 6
2 References . 6
2.1 Normative references . 6
2.2 Informative references . 6
3 Definition of terms, symbols and abbreviations . 6
3.1 Terms . 6
3.2 Symbols . 6
3.3 Abbreviations . 7
4 General requirements . 7
4.1 Background . 7
4.2 Autonomous optical network management, control and operation functions . 7
5 Overview of general Autonomous Network level classification . 8
5.1 Overview . 8
5.2 General dimensions of Autonomous Network level classification . 8
5.3 General method of Autonomous Network level classification . 9
5.4 Methodology to define fixed network Autonomous Network levels . 10
6 Fixed network Autonomous Network architecture and operation processes . 11
6.1 Fixed network Autonomous Network architecture overview . 11
6.2 Core operation workflows of fixed network Autonomous Network . 12
7 Scenario-based fixed network Autonomous Network level classification . 13
7.1 Autonomous Network level classification for Optical Transport Network . 13
7.1.1 Planning and deployment . 13
7.1.1.1 Operational sub-tasks . 13
7.1.1.2 Autonomous Network level classification . 14
7.1.2 Fulfilment . 16
7.1.2.1 Operational sub-tasks . 16
7.1.2.2 Autonomous Network level classification . 17
7.1.3 Maintenance . 19
7.1.3.1 Operational sub-tasks . 19
7.1.3.2 Autonomous Network level classification . 21
7.1.4 Optimization . 23
7.1.4.1 Operational sub-tasks . 23
7.1.4.2 Autonomous Network level classification . 25
7.2 Autonomous Network level classification for Access and Residential Networks . 27
7.2.1 Planning and deployment . 27
7.2.1.1 Operational sub-tasks . 27
7.2.1.2 Autonomous Network level classification . 28
7.2.2 Fulfilment . 31
7.2.2.1 Operational sub-tasks . 31
7.2.2.2 Autonomous Network level classification . 32
7.2.3 Maintenance . 34
7.2.3.1 Operational sub-tasks . 34
7.2.3.2 Autonomous Network level classification . 36
7.2.4 Optimization . 39
7.2.4.1 Operational sub-tasks . 39
7.2.4.2 Autonomous Network level classification . 41
8 Fixed network Autonomous Network level evaluation . 44
8.1 Overview of fixed network Autonomous Network evaluation . 44
8.2 Fixed network Autonomous Network evaluation methodology . 44
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8.2.1 Overview of evaluation steps . 44
8.2.2 Step 1: Determine the evaluation objects . 45
8.2.3 Step 2: Select the evaluation scenarios . 46
8.2.4 Step 3: Map to standard operational sub-tasks . 46
8.2.5 Step 4: Score the evaluation object . 46
8.2.6 Step 5: Output the evaluation conclusion . 47
History . 48

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Intellectual Property Rights
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Foreword
This Group Report (GR) has been produced by ETSI Industry Specification Group (ISG) Fifth Generation Fixed
Network (F5G).
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.

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1 Scope
The present document defines the ETSI ISG F5G Autonomous Network features for different ETSI ISG F5G fixed
network generations, to provide an evaluation basis for measuring the Autonomous Network level of a fixed network
along with its components and workflows. These features include the intelligent characteristics of each Autonomous
Network level (from L0 to L5) and the operators' operational management process. The present document also defines
the evaluation methodology to score the level of specific systems.
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] TM Forum IG1230 (V1.1.1): "Autonomous Networks Technical Architecture".
[i.2] TM Forum IG1218 (V2.2.0): "Autonomous Networks - Business requirements & architecture".
3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the following terms apply:
autonomous network: See the definition of "Autonomous Network" in the Terminology of TM Forum IG1230 [i.1].
closed loop: See the definition of "Closed Loop" in the Terminology of TM Forum IG1230 [i.1].
general task: one of intent translation, awareness, analysis, decision and execution
general workflow: set of general tasks forming a complete closed loop management system from receiving network
management and operation requirements to realizing those requirements in the deployed network
operation workflow: one of planning, deployment, fulfilment, maintenance and optimization
operational sub-task: sub-task in an operation workflow
3.2 Symbols
Void.
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3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
AI Artificial Intelligence
API Application Programming Interface
CPE Customer Premise Equipment
CPU Central Processing Unit
DBA Dynamic Bandwidth Assignment
E-ONU Edge Optical Network Unit
F5G Fifth Generation Fixed Network
F5G-A Fifth Generation Fixed Network Advanced
FTTR Fibre-To-The-Room
GUI Graphical User Interface
HQoS Hierarchical Quality of Service
KPI Key Performance Indicator
LOF Loss Of Frame
LOS Loss Of Signal
NE Network Element
OA Optical Amplifier
OCh Optical Channel
ODN Optical Distribution Network
OLT Optical Line Terminal
ONU Optical Network Unit
OPEX OPerational EXpenditure
OTN Optical Transport Network
PON Passive Optical Network
P-ONU Primary Optical Network Unit
SDO Standards Development Organization
SLA Service Level Agreement
4 General requirements
4.1 Background
The Artificial Intelligence (AI) technology is continuing to develop rapidly, and has been successfully applied in many
technical areas, greatly promoting the implementation and application of AI in various industries. At present, the
application of AI technology in telecom networks is also being studied by the telecom industry, and related standards
are evolving in the related Standards Development Organizations (SDOs).
Once SDN technology was introduced in the optical networks, the optical network management and control technology
began to evolve towards being more intelligence orientated. AI technologies make full use of the optical network
management data to improve the efficiency of optical network management, control and operation.
Current research focuses mainly on developing technical solutions and algorithms to apply AI in the optical networks.
There is insufficient research on providing uniform standards to evaluate how intelligent an optical network is. The
present document provides an analysis of the approach and tools used for that purpose.
4.2 Autonomous optical network management, control and
operation functions
The core functions of optical network management, control and operation include:
• Network planning
• Network deployment
• Network fulfilment
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• Network maintenance
• Network optimization
The key aspects of autonomous management, control and operation of an optical network are:
• Planning: to provide optimal network planning, to improve the utilization of network resources while
satisfying the service development requirements.
• Deployment: to automatically and accurately deploy the planned network, and to significantly reduce the
deployment time.
• Fulfilment: to automatically provision the optical services, improving users' experiences.
• Maintenance: to identify network faults or risks, and to rectify the faults / eliminate the risks in a timely
manner.
• Optimization: to improve the resource utilization and service quality, and to improve the resilience of the
optical network.
The present document provides the classification and evaluation of the Autonomous Network levels for the fixed optical
network management, control and operation, with the intent to guide the industry in the development of intelligent
optical networks. The benefits are:
• Providing the industry with an evaluation consensus basis on measuring the autonomous capability of an
optical network (and its components).
• Providing guidance to the industry to develop roadmaps, phased objectives, relevant strategies and plans
towards an intelligent optical network.
• Providing decision-making assistance to network operators, vendors and other industry participants in
technology choice and product planning on the aspect of network intelligence.
5 Overview of general Autonomous Network level
classification
5.1 Overview
The Autonomous Network level classification system provides a common understanding of how intelligent a network
is. The most important factors to evaluate the Autonomous Network levels are human participation and systems
involvement in the network management, control and operation. The higher the level of Autonomous Network, the
fewer are the manual workflows involved.
5.2 General dimensions of Autonomous Network level
classification
The Autonomous Network level classification and evaluation involves complex workflows, and therefore needs to be
measured by multiple scenarios and dimensions.
TM Forum IG1230 [i.1] defines the general workflow of network management, control and operation, as shown in
Figure 7-2 of TM Forum IG1230 [i.1]. The present document uses this general workflow as the key evaluation
dimensions for the fixed network Autonomous Network level classification.
In the Autonomous Network level classification system, a general workflow is composed of multiple general task types,
which form a complete closed loop management system from receiving network management and operation
requirements to realizing those requirements in the deployed network. The autonomy capabilities of the tasks in a
general workflow are the most important factors that impact the network autonomy level.
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The general workflow of network management, control and operation includes the following five tasks types:
1) Intent translation: As defined in TM Forum IG1230 [i.1], an intent is a formal specification of the expectation,
including requirements, goals and constraints, given to a technical system. The intent translation is a set of
tasks which convert the operator or customer's intent into detailed management operations and policies, and
receive the intent fulfilment feedback results.
2) Awareness: Collecting the raw network data, and pre-processing that data to perceive network information
(including network performance, network anomalies, network events, etc.).
EXAMPLE: Pre-processing data such as data cleaning, enhancement, and statistics.
3) Analysis: Analysing the data, which has been collected from the network, in the awareness phase to
understand the current network status, predict future trends based on the historical data, and generate
operational options that help satisfy network management, control and operation requirements.
4) Decision: Based on the operational options or suggestions provided by the analysis phase, determining the
most suitable executable management operations, to satisfy the network management and operation
requirements.
5) Execution: Execute the management operations based on the decisions made in the decision phase.
See more detailed description of the general workflow and tasks are defined in TM Forum IG1230 [i.1].
5.3 General method of Autonomous Network level classification
TM Forum IG1230 [i.1] defines the Autonomous Network levels framework (L0 to L5), based on human participation
and the systems involved in the general network management workflow. Table 1 is the Autonomous Network Levels
Framework based on TM Forum IG1230 [i.1]. In this table, the level evaluation criteria for each type of general tasks
are determined by "P", "S" and "P/S", where "P" indicates that the related tasks are performed by humans, "S" indicates
that the related tasks are automatically performed by the telecom system, and "P/S" indicates that the related tasks are
performed by the cooperation of human and the telecom system.
Table 1: Autonomous Network Levels Framework based on TM Forum IG1230 [i.1]
L0 L1 L2 L3 L4 L5
Autonomous Manual Assisted Partial Conditional High Full
Levels Operation & Operation & Autonomous Autonomous Autonomous Autonomous
Maintenance Maintenance Networks Networks Networks Networks
Execution
P P/S S S S S
Awareness P P/S P/S S S S
Analysis P P P/S P/S S S
Decision P P P P/S S S
Intent/Experience P P P P P/S S
Applicability N/A Selected Scenarios All Scenarios
P: People (manual) and S: Systems (autonomous)

Based on TM Forum IG1230 [i.1], the detailed definition of each Autonomous Network level (L0 to L5) is following:
• Level 0 - Manual Operation & Maintenance: The system delivers assisted monitoring capabilities, which
means all dynamic tasks have to be executed manually.
• Level 1 - Assisted Operation & Maintenance: The system executes a certain repetitive sub-task based on
pre-configuration to increase execution efficiency.
• Level 2 - Partial Autonomous Networks: The system enables closed loop O&M for certain units based on the
AI model under certain external environments.
• Level 3 - Conditional Autonomous Networks: Building on L2 capabilities, the system with awareness senses
real-time environmental changes, and in certain network domains, optimize and adjust itself to the external
environment to enable intent-driven closed loop management.
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• Level 4 - High Autonomous Networks: Building on L3 capabilities, in more complicated cross-domain
environment, the system enables analyse and make decisions based on predictive or active closed loop
management of service and customer experience-driven networks.
• Level 5 - Full Autonomous Networks: This level is the end-goal for telecom network evolution. The system
possesses closed loop automation capabilities across multiple services, multiple domains, and the entire
lifecycle, achieving an autonomous network.
For more detailed description of the general Autonomous Network levels see TM Forum IG1230 [i.1].
5.4 Methodology to define fixed network Autonomous Network
levels
The present document uses the above general level definitions as the basis for the fixed network Autonomous Network
level classification.
The present document focuses on the Autonomous Network level classifications of the Optical Transport Network and
the Access and Residential Networks, which are defined in clauses 7.1 and 7.2 of the present document respectively.
Figure 1 illustrates the methodology used in the present document to define the fixed network Autonomous Network
levels.
• Step 1: Identifies the fixed network operation workflows (including the planning and deployment, fulfilment,
maintenance, and optimization).
• Step 2: Breaks down each operation workflow into multiple operational sub-tasks.
• Step 3: Maps these operational sub-tasks to different types of general tasks (intent translation, awareness,
analysis, decision and execution) in the general workflow.
• Step 4: Defines the detailed Autonomous Network levels for each operational sub-task, based on the level
evaluation criteria (i.e. "P", "S" or "P/S") defined in Table 1.

Figure 1: Methodology to define the fixed network Autonomous Network levels
With the Autonomous Network level definition of the fixed networks, the comprehensive score of the Autonomous
fixed network levels (L0 to L5) in different scenarios is measured and evaluated. Clause 8 of the present document
provides the Autonomous Network evaluation methodology of the fixed networks.
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6 Fixed network Autonomous Network architecture and
operation processes
6.1 Fixed network Autonomous Network architecture overview
TM Forum IG1218 [i.2] defines the general an Autonomous Network framework, as shown in Figure 6 of TM Forum
IG1218 [i.2]. This framework includes three layers and four closed loops. The three layers from top to bottom are:
1) Business operation layer.
2) Service operation layer.
3) Resource operation layer.
The four closed loops, which fulfil the full lifecycle of the interlayer interaction, are:
1) User closed loop.
2) Business closed loop.
3) Service closed loop.
4) Resource closed loop.
Figure 2 shows the fixed network Autonomous Network architecture, which is based on the general Autonomous
Networks framework defined in TM Forum IG1218 [i.2]. In this architecture, the network management and control
layer corresponds to the Autonomous Network resource operation layer. It contains multiple network management and
control systems, each of which is used to manage and control a single self-operating optical autonomous domain,
forming a single-domain autonomy. The network orchestration layer corresponds to the Autonomous Network service
operation layer, which performs the multi-domain network planning, deployment, fulfilment, maintenance and
optimization. The application layer corresponds to the Autonomous Network business operation layer, which provides
the business capabilities and the service operation.

Figure 2: Fixed network Autonomous Network architecture
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6.2 Core operation workflows of fixed network Autonomous
Network
As described in TM Forum IG1230 [i.1], the full life-cycle of the network management, control and operation is divided
into five general operation workflows: planning, deployment, fulfilment, maintenance and optimization. In addition, as
a basic function of the network operation, the network resource management is involved in all the above five operation
workflows.
Based on the general operation workflows defined in TM Forum IG1230 [i.1], the fixed network core operation
workflows are categorized as follows:
• Planning:
The network planning function gains insight into key information such as coverage and high-value user
distribution, provides network planning options, and evaluates whether the planned solution satisfies network
and service requirements. The core objective of network planning is to have the best utilization of network
resources.
• Deployment:
The optical network deployment refers to on-site hardware and software installation and configuration, and the
optical performance commissioning based on the result of the network design, as well as the network
verification and the on-site acceptance. The core objective of network deployment is to accurately deploy the
network in accordance with the network planning. The deployment time should be as short as possible.
NOTE 1: Network planning and deployment are highly related to each other. In clause 7 of the present document,
these two operation workflows are put together to define their Autonomous Network Levels.
• Fulfilment:
The procedure for service fulfilment includes receiving user's service provisioning requests, developing and
determining the service provisioning solutions, finally configuring and verifying the service in the network.
• Maintenance:
Maintenance refers to network inspection, risk identification and elimination, network status monitoring, and
network fault detection, prediction and troubleshooting.
NOTE 2: Network inspection includes network equipment inspection (i.e. checking the equipment information to
detect hardware or software risk), and on-site inspection (e.g. inspecting the equipment room and the fibre
connections to detect related risks).
NOTE 3: Network fault detection, prediction and troubleshooting includes alarm information gathering, root alarm
analysis, root cause analysis, network or service recovery, and fault recovery. Typical examples of optical
network faults are: Optical Transport Network (OTN) / Passive Optical Network (PON) equipment fault
or link fault, fibre attenuation deterioration, wavelength performance deterioration, and laser or board
level hardware error.
• Optimization:
The optimization refers to detecting network quality problems, analysing the root causes, and determining and
implementing optimization solutions to meet the requirements of users' service experience and operators'
resource utilization.
NOTE 4: Typical network quality problems include performance quality problems (e.g. increased packet delay and
packet jitter, intermittent disconnection, packet loss, optical-layer performance deterioration or excessive
bit errors), and network resource utilization problems (e.g. unbalanced traffic load, low resource
utilization, or suboptimal route problem).
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7 Scenario-based fixed network Autonomous Network
level classification
7.1 Autonomous Network level classification for Optical
Transport Network
7.1.1 Planning and deployment
7.1.1.1 Operational sub-tasks
The planning and deployment operation workflow of the optical transport network is divided into six operational
sub-tasks:
• Network requirement prediction
• Resource determination and analysis
• Network planning solution development
• Network planning decision
• Integrated configuration
• On-site acceptance
These six sub-tasks are mapped to the five different general tasks (intent translation, awareness, analysis, decision and
execution) in the Autonomous Network general workflow, as shown in Figure 3.

Figure 3: Optical Transport Network planning and deployment operational sub-tasks and their
mapping to the general tasks in the Autonomous Network general workflow
• Intent translation:
- Network requirement prediction: Output the network planning requirements to the network planner or
to the system, based on multiple factors including users' business intentions, network operator's service
development objectives and network deployment plans.
EXAMPLE 1: Network planning requirements may be network coverage and capacity requirements, resiliency to
name a few.
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• Awareness:
- Resource determination and analysis: Determine the resource usage of the current network and
analyse the gap between the network planning requirements and the current network resource status.
• Analysis:
- Network planning solution development: Output the overall network planning result to the network
planner (as document) or to the system (in a machine-readable format), based on the network planning
requirements and the determination and analysis of the current network resource.
• Decision:
- Network planning decision: Based on the outcome of the network planning and the simulation results,
evaluate whether the network planning requirements are satisfied.
• Execution:
- Integrated configuration: Complete onsite hardware and software installation deployment based on the
network planning decision, to ensure that all the Network Elements (NEs) are operating and managed
correctly. Complete the initial configuration of the optical network.
EXAMPLE 2: Complete the initial configuration of the optical network e.g. logical fibre connection
configuration and optical performance commissioning, to name a few.
- On-site acceptance: Tests and accepts the deployed optical transport network (including the fibre
connection, the service connectivity, the optical-layer performance, and the software versions).
EXAMPLE 3: Testing and acceptance of an optical transport network deployment use loopbacks, metering and
querying of the network.
7.1.1.2 Autonomous Network level classification
The Autonomous Network level (from L0 to L5) classification for the Optical Transport Network planning and
development is determined based on the participation of human and automation systems.
Table 2 describes the Autonomous Network levels for the six operational sub-tasks (network requirement prediction,
resource determination and analysis, network planning solution development, network planning decision, integrated
configuration, and on-site acceptance) for the Optical Transport Network planning and development.
Table 2: Autonomous Network level classification
for the Optical Transport Network planning and development
Operational
L0 L1 L2 L3 L4 L5
sub-tasks
1. The system
automatically collects
1. The system
the current status
automatically
1. Use 1. The system information of the
collects the
auxiliary tools automatically network, generates
current status
to collect the collects the
statistics and
information of
Network
Manually current status current status performs analysis.
the network, and
requirement analyse and information of information of 2. The system uses
generates
prediction predict the the network. the network. intelligent
preliminary
(Intent network 2. Manually 2. Manually technologies to
statistics.
translation) requirements. analyse and analyse and automatically predict
2. Manually
predict the
predict the the network
analyse and
network network requirements.
predict the
requirements. requirements. (EXAMPLE 1: service
network
growth trend and
requirements.
resource requirement
prediction.
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Operational
L0 L1 L2 L3 L4 L5
sub-tasks
1. The system
automatically
obtains the
online physical
1. The system resource
automatically information
1. Use
obtains the (active
auxiliary tools
online physical resources). In addition to the
to obtain the
resource 2. The system criteria in L3, the
online physical
information automatically system performs
Manually resource
Resource (active generates resource prediction
determine the information
determination resources). statistics and and resource
resource (active
and analysis
2. The system performs bottleneck
allocation and resources).
(Awareness) automatically analysis of the identification,
analysis. 2. Manually
generates including resource
resource usage.
determine the
statistics and EXAMPLE 2: availability and
resource Full-scenario
performs slots, ports, service availability.
allocation and
and
analysis of the bandwidth, and
analysis. full-lifecycle
resource wavelength
automation.
usage. channels.
The system
3. The system
automatically
automatically
performs the
analyses the
network
network latency.
requirement
The system
prediction, the
automatically
resource
develops the
determination
greenfield or
and analysis,
capacity
the network
expansion
planning
planning
Manually solution
The system solution,
develop the development
develops the including:
planning Based on the and decision,
Network network
(a) service route
Manually solution with planning solution, the the integrated
planning planning recommendation
develop the templates and system further configuration,
solution solution based (EXAMPLE 4:
planning auxiliary tools. performs service and the on-site
development
on fixed rules, computed by
solution. EXAMPLE 3: survivability analysis acceptance.
(Analysis) assisting with shortest path or
historical by fault simulation. Support
the manual minimum hop
project case automatic
development. number).
library. online learning
(b) Optical
and
Channel (OCh)
optimization
planning
for AI model
(EXAMPLE 5: its
iteration.
centre frequency
and spectrum
width).
1. Based on the
The system
1. Manually configured rules,
automatically
adjust the the system
optimizes the
solution automatically
solutions, and
Manually make developed by evaluates the
Network determines the
decisions the system. network planning
planning Same criteria optimal solution
based on 2. Manually solutions and
decision as L0. among the
expert make provides
(Decision)
alternatives.
experience. decisions suggestions.
EXAMPLE 6: optimal
based on 2. Manually
Optical Amplifier (OA)
expert make decisions
configuration and
experience. based on expert
regenerator locations.
experience.
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Operational
L0 L1 L2 L3 L4 L5
sub-tasks
1.Automatic
1.Automatic
configurations of configurations by the
1. Manual
the system. system.
configuration
EXAMPLE 7: EXAMPLE 8:
Manually apply using auxiliary
automatic automatic CPE go-
the script on tools and
Customer online configuration.
site based on systems.
Premise 2. The system
Integrated Manual the work order, 2. Manually
Equipment automatically
configuration integrated the and manually commission
(CPE) go-online commissions the
(Execution) configuration. commission the optical-
configuration. optical-layer
the optical- layer
2. The system performance
layer performance
commissions the (including the
performance. using auxiliary
optical-layer commissioning of the
tools and
performance optical paths in
systems.
with manual wavelength expansion
assistance. scenario).
1. The on-site
tools
1. The on-site
automatically 1. The system
tools
perform site automatically exports
automatically
acceptance and network performance
Manual on-site perform single-
transmit the data and performs
On-site
acceptance site
Manual on-site acceptance data network performance
acceptance based on acceptance.
acceptance. back to the acceptance.
(Execution) instruments 2. The tools
system. 2. The system
and tools. automatically
2. The system automatically
generate an
automatically generates an
acceptance
generates the
acceptance report.
report.
acceptance
report.
7.1.2 Fulfilment
7.1.2.1 Operational sub-tasks
The main fulfilment operation scenario is the service provisioning. The fulfilment operation workflow of the optical
transport network is divided into six operational sub-tasks:
• Service provisioning intention analysis
• Resource confirmation
• Service configuration solution development
• Service configuration decision
• Service configuration activation
• Service testing
These six sub-tasks are mapped to the five different general tasks (intent translation, awareness, analysis, decision and
execution) in the Autonomous Network general workflow, as shown in Figure 4.
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Figure 4: Optical Transport Network fulfilment operational sub-tasks and their mapping to the
general tasks in the Autonomous Network general workflow
• Intent translation:
- Service provisioning intention analysis: Analyse the service provisioning requirements and translate
them into network requirements
EXAMPLE 1: Network requirements such as bearer network type, protection requirements, and Service Level
Agreement (SLA) (e.g. latency and bandwidth) assurance policies.
• Awareness:
- Resource confirmation: Perform network resource analysis, based on user's service requirements and
real-time network status.
EXAMPLE 2: Network resource analysis may include resource status, available ports, link bandwidth, resource
usage, and latency.
• Analysis:
- Service configuration solution development: Develop the service configuration solutions and emulate
the services based on the resource confirmation result.
• Decision:
- Service configuration decision: Determine the final service configuration solution, ensuring that the
service provisioning requirements are satisfied.
• Execution:
- Service
...