IEEE IM 2019 – Washington DC, USA (link to papers)
Following IM 2017 in the picturesque Lisbon, one of the most beautiful cities in Europe, this year’s event was held in the US capital city during its peak cherry blossom season.



The conference adopted the theme of “Intelligent Management for the Next Wave of Cyber and Social Networks”. Besides the regular tracks, the five-day conference features some great tutorials, keynotes and panels. I have pages of notes and many contacts to follow up.

A few highlights are: Zero-touch network and service management (and how it’s actually “touch less” rather than touchless!), Huawei’s Big Packet Protocol (network management via packet header programming), DARPA’s Off-planet network management (fractionated architectures for satellites), Blockchain’s social, political, regulatory challenges (does not work with GDPR?) by UZH, Data science/ML for network management from Google and Orange Labs (with some python notebooks and a comprehensive survey paper of 500+ references.) and many more. I am hoping to write more about some of them in the future when I have a chance to study them further. There are certainly some good topics for student projects.
Since I am linked to both the multimedia/HCI and communication network communities, I have the opportunity to observe different approaches and challenges faced by these communities towards AI and ML. In multimedia communities, its relatively easy to acquire large and clean datasets, and there is a high level of tolerance when it comes to “trial and error”: 1) No one will get upset if a few from a hundred image search results are not accurate and 2) you can piggy-back some training module/reinforced learning on your services to improve the model. Furthermore, applications are often part of a closed proprietary environment (end to end control) and users are not that bothered with giving up their data. In networking, things are not far from “mission impossible”. 95% accuracy in packet forwarding will not get you very far, and there is not much infrastructure available to track any data, let alone making any data open for research. Even when there are tools to do so, you are likely to encounter encryption or information that is too deep to extract in practice. Also, tracking network data seems to attracts more controversy. We have a long and interesting way to go.



Washington, D.C. is surrounded by some amazing places to visit. George Washington’s riverside Mount Vernon is surely worth a trip. Not far from the Dulles airport is the Great Falls Park with spectacular waterfalls on Potomac river that separate Maryland and Virginia. Further west is the 100-mile scenic Skyline Drive and Appalachian Trail in Shenandoah National Park.
Reblogged this on SDCN: Software Defined Cognitive Networking.