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Network Management (nmrg)

RG Name Network Management
Acronym nmrg
State Active
Charter charter-irtf-nmrg-02 Approved
Document dependencies
Additional resources Wiki, Zulip stream
Personnel Chairs Jérôme François, Laurent Ciavaglia
Secretaries Jéferson Campos Nobre, Pedro Martinez-Julia
Mailing list Address
To subscribe
Chat Room address

Charter for Research Group

The Network Management Research Group (NMRG) provides a forum for
researchers to explore new technologies for the management of the Internet.
In particular, the NMRG will work on solutions for problems that are not
yet considered well understood enough for engineering work within the IETF.

The focus of the NMRG will be on management services that interface with
the current Internet management framework. This includes communication
services between management systems, which may belong to different
management domains, as well as customer-oriented management services. The
NMRG is expected to identify and document requirements, to survey possible
approaches, to consider new architectural frameworks, to provide
specifications for proposed solutions, and to prove concepts with prototype
implementations that can be tested in large-scale real-world environments.

The IETF Operations and Management Area Directors are members of the NMRG
mailing list and invited to NMRG meetings in order to ensure free flow of
information in both directions, and to avoid duplication of work with the
various IETF working groups.

The group will report its progress through a publicly accessible web site
and presentations at IETF meetings. Specifications developed by the NMRG
will be submitted for publication as Experimental or Informational RFCs.


Membership in the NMRG is open to all interested parties.


Regular working meetings are held about three to five times per year at
locations convenient to the majority of the participants. Working meetings
vary from hours-long working sessions (typically when held as part of IETF
meetings) to days-long meetings when co-located with conferences or events
related to network management.

Regular virtual meetings are also organized on a monthly or per-need basis.

Research Activities (2017-2022)

The constant evolution of networking technologies, in scale, versatility,
and heterogeneity, generates operational complexity and demands novel
disruptive management solutions to address it. The NMRG will prioritize
investigation of three related topics: 1) self-driving/-managing networks,
2) intent-based networking and 3) artificial intelligence in network
management. Note: beyond these three topics, the NMRG remains open to
presentation of other topics of interest.

While the ultimate goal of self-driving/-managing networks is fully
autonomous network operations, there will be intermediate levels where the
human users remain “in the loop” and are progressively assisted and
replaced by more and more intelligent mechanisms. Interfaces between humans
and a self-driving system are important and required to allow bidirectional
communications. On one hand, the user must be able to express guidance and
its needs without having to handle the full complexity of the underlying
infrastructures. On the other hand, users must understand the decisions
which were taken and the reasons why, be informed about the future actions
the system will initiate and also be provided with recommendations.

In this area, Intent-Based Networking (IBN) provides high-level,
user-friendly abstractions to describe business and operational goals, and
alleviates the need for the user to know and derive the technical details
on how to achieve those goals. IBN is an essential component of
self-driving networks but requires the introduction of intelligent
mechanisms to properly process intents with as little human involvement as

Certainly, some of those intelligent mechanisms can rely on advances in
(but should not be limited to) Artificial Intelligence (AI). While
different forms of AI have been used for decades in network management, the
combined progress in amount of data, computing power, AI algorithms and
flexible capabilities of networks in recent years makes highly relevant to
re-examine in depth the coupling between AI and network management.

Work plan

To investigate these topics, the initial set of work items comprises:

  • For Intent-Based Networking (IBN):
  1. Document the problem statement, design goals and challenges.
    Goal: describe the problem and solution spaces; identify the limits
    of current technologies and methods and derive the associated
    research challenges.

  2. Document fundamental concepts, background, and terminology.
    Goal: provide clarity and achieve a common understanding of the
    various concepts, definitions and terms of what constitutes an IBN

  3. Develop a taxonomy and document suitable means to express intents.
    Goal: categorize the different forms of intents and define what
    constitutes a “well-formed” intent; describe how an intent can be
    expressed and what can be expressed using an intent with means such
    as information models, grammars, and languages.

  4. Design and specify a common architectural framework comprising
    requirements, functions and techniques to realize an archetypal
    IBN system; describe the life-cycle and theory of operations.
    Goal: determine the elementary functional blocks of an IBN system,
    their interactions, inputs and outputs; propose different techniques
    applicable for the different functions.

  5. Define appropriate validation scenarios and use cases describing
    concrete examples of intent expressions and functions.
    Goal: assess the quality and completeness of specifications and
    evaluate intent-based systems functionalities in experimental

  6. Develop implementations and proof of concepts.
    Goal: demonstrate the feasibility of the proposed framework and its
    functions; detect potential design flaws, and provide a basis for
    interoperability evaluations.

  7. Study the integrability and interoperability aspects of the proposed
    IBN architectural framework.
    Goal: enable the large adoption and applicability of IBN with
    existing and emerging technologies, and provide guidance on
    deployment considerations.

For Artificial Intelligence in Network Management (AI-NM):

  1. Investigate, organize and document the major research challenges in
    AI for Network Management.
    Goal: provide a reference document which defines the different forms
    and usages of AI in network management and articulates the different
    goals, challenges, requirements and research directions.

  2. Organize and animate a series of practical Network Management AI
    Goal: promote experimental research, practical knowledge and
    validation of AI techniques to solve network management problems and
    foster exchanges and cross-participation of both AI and Network
    Management specialists.

  3. Support discussion and collaboration on techniques, (meta-)data,
    experimentations and best practises for the use and integration
    of AI with networking management approaches.
    Goal: offer a forum for the Network Management AI community to report
    on advances, developments and key results and introduce its efforts
    to the IETF. Note: Applicability of AI techniques for IBN
    functionalities and mechanisms is an example of potential joint
    activity between the Network Management AI and IBN realms.

For Self-Driving/-Managing Networks (SD/MN):

  1. Support discussion to develop a common understanding of the
    problem-solution space on new architectural frameworks, articulate
    related requirements, survey and propose possible novel approaches.
    Goal: offer a venue for the Network Management community to debate on
    current Internet management frameworks and new proposals, and how to
    adapt and anticipate on needs, technologies and ecosystem evolution.

  2. Investigate and document reference models and de-facto best practises.
    Goal: describe how various realms and components, such as
    intent-based functionality, automation and zero-touch capabilities,
    or else algorithmic approaches (AI or non-AI based), compose together
    to form modern, comprehensive and coherent management solutions.


Date Milestone Associated documents
Nov 2021 Document(s) for IBN work item 7 submitted to IRSG review
Nov 2021 Document(s) on IBN work items 5-6 submitted to IRSG review
Jul 2021 Second set of results and report on AI-NM work item 2 published (i.e. Challenge #2)
Jul 2021 Document(s) for IBN work item 4 submitted to IRSG review
Mar 2021 Document(s) on AI-NM work item 1 submitted to IRSG review
Mar 2021 Document(s) for IBN work item 7 submitted to RG adoption
Nov 2020 First set of results and report on AI-NM work item 2 published (i.e. Challenge #1)
Nov 2020 Document(s) on IBN work items 5-6 submitted to RG adoption
Nov 2020 Document(s) for IBN work items 1-3 submitted to IRSG review
Jul 2020 Intermediate results on IBN work items 5-6 communicated
Jul 2020 Document(s) for IBN work item 4 submitted to RG adoption
Mar 2020 Framework for AI-NM work item 2 published
Mar 2020 Document(s) on AI-NM work item 1 submitted to RG adoption
Nov 2019 Preliminary results on IBN work items 5-6 communicated
Nov 2019 Document(s) for IBN work items 1-3 submitted to RG adoption