My previous blog post was about the IETF BoFs, but there are also new meetings in the research arm of the IETF, the IRTF. The proposed Measurement and Analysis for Protocols (MAPRG) research group is meeting for the first time in Buenos Aires. Another proposed research group, the Network Machine Learning (NMLRG) is also meeting in Buenos Aires, and this is their second meeting.
This is what the planned charter says about the role of the MAPRG:
Our Internet has grown into something that differs from what was envisioned. Its protocols sometimes operate in an environment other than than that for which they were designed. For instance, some network elements treat some protocols differently than others and those protocols themselves are sometimes reused and abused in ways initially unforeseen. The Measurement and Analysis for Protocols (MAP) Research Group (RG) explores such phenomena by measurement with the aim to inform protocol engineering and practice.
Many protocol engineering efforts in a standards development context, as well as best practices for the operation of IETF-defined protocols, can benefit from insight provided by Internet measurements of various kinds. Likewise, Internet measurement research efforts can stand to gain from contacts with the IETF. The Measurement and Analysis for Protocol Engineering (MAP) Research Group aims to provide a forum for interchange between these two communities.
And this is what the NMLRG plans to do:
Machine learning technologies can learn from historical data, and make predictions or decisions, rather than following strictly static program instructions. They can dynamically adapt to a changing situation and enhance their own intelligence with by learning from new data. This approach has been successful in image analysis, pattern recognition, language recognition, conversation simulation, and many other applications. It can learn and complete complicated tasks. It also has potential in the network technology area. It can be used to intelligently learn the various environments of networks and react to dynamic situations better than a fixed algorithm. When it becomes mature, it would be greatly accelerate the development of autonomic networking.
The Network Machine Learning Research Group (NMLRG) provides a forum for researchers to explore the potential of machine learning technologies for networks. In particular, the NMLRG will work on potential approaches that apply machine learning technologies in network control, network management, and supplying network data for upper-layer applications.
I think these are very exciting topics! Hopefully you all can join the meetings of these groups! The MAP RG is currently scheduled for Monday 15:50-17:20, but schedules may still change. The NMLRG is currently scheduled for Thursday 10:00-12:30. Registration for the meeting is open at the IETF meeting page. It is also possible to follow and participate the meeting remotely.
Jari Arkko, IETF Chair