FCAI SIG

Edge AI

This SIG is aimed to harness the synergy between AI and Edge computing and improving the interaction between two flagships: the 6G flagship, and the FCAI flagship. Edge computing is revolutionizing communication networks and is expected to be a key component of next generation network. AI solutions can benefit by harnessing the potential of Edge Computing, and edge computing processes can benefit by AI. This page highlights how each of our research program interacts with Edge Computing within FCAI and lists the groups currently involved.

This SIG will help organize events that improve the synergy between the 6G and FCAI flagships. It will provide a platform for discussing the impact edge computing and AI have on each other.

This SIG is aimed to harness the synergy between AI and Edge computing and improving the interaction between two flagships: the 6G flagship, and the FCAI flagship. Edge computing is revolutionizing communication networks and is expected to be a key component of next generation network. AI solutions can benefit by harnessing the potential of Edge Computing, and edge computing processes can benefit by AI. This page highlights how each of our research program interacts with Edge Computing within FCAI and lists the groups currently involved.

This SIG will help organize events that improve the synergy between the 6G and FCAI flagships. It will provide a platform for discussing the impact edge computing and AI have on each other.

We also have a mailing list fcai6g-sig-edgeai@helsinki.fi. You can subscribe to this mailing list by sending an email to majordomo@helsinki.fi with the following command in the body of your email message: subscribe fcai6g-sig-edgeai. This mailing list will be primarily used to notify the upcoming events.

We also request you to join the slack workspace edgeai-oulu.slack.com

Coordination: Professor Sasu Tarkoma (University of Helsinki), Professor Ella Peltonen (University of Oulu), Dr. Xiaoli Liu (University of Helsinki)

Research

The SIG will work on the following two closely related research programs:

Edge for AI

The edge computing paradigm enables offloading computation for latency critical applications, and this offers AI applications the benefits of harnessing resources placed at the network edge.   Research areas in this program include distributed AI, federated learning, computation offload.

AI for edge

The edge is expected to offer a vast number and a vast variety of resources, and efficiently managing their lifecycle will require AI. This program focuses on leveraging AI on tasks related to the lifecycle of Edge computing which includes placement, monitoring, reconfiguration, and optimizing usage of the edge resources.

People