Monday, May 17, 2021
18:30PM - 20:00PM (webex link)
The Network Management Research Group (NMRG) of the Internet Research Task Force (IRTF) 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. Nevertheless, opportunities for standardization regularly emerge thanks to the closeness with the IETF.
The general objective of NMRG is thus to foster collaboration between researchers and engineers from both industry and academia. In that respect, the NMRG is complementary to activities in conferences because research work, even in its earlier stages, can be introduced to a different type of audience and contributions can be refined in a continuous manner thanks to the advices and guidance of the group.
NMRG @ IM 2021
The meeting will introduce the work of the IRTF in general, and technical activities of the NMRG in particular; highlighting opportunities for research and collaborations. Technical presentations on selected topics will also be part of the meeting.
The meeting agenda and materials are available at: https://datatracker.ietf.org/meeting/interim-2021-nmrg-02/session/nmrg
Further details on the NMRG are available its homepages: https://trac.ietf.org/trac/nmrg/wiki/WikiStart and https://datatracker.ietf.org/group/nmrg/documents/
NMRG 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:
- self-driving/-managing networks,
- intent-based networking and
- artificial intelligence in network management.
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 possible.
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.