Bio: Igor Kadota is an Assistant Professor of Electrical and Computer Engineering at Northwestern University. Previously, he was a Postdoctoral Research Scientist at Columbia University. He received the Ph.D. degree from MIT LIDS and his B.Sc. degree from the Aeronautics Institute of Technology (ITA) in Brazil. His research is on modeling, analysis, optimization, and implementation of next-generation communication networks, with the emphasis on advanced wireless systems and time-sensitive applications. Igor was a recipient of several research, mentoring, teaching, and service awards, including the 2018 Best Paper Award at IEEE INFOCOM, the 2019 Best Paper Finalist at ACM MobiHoc, the 2020 MIT School of Engineering Graduate Student Extraordinary Teaching and Mentoring Award, and he was selected as a 2022 LATinE Trailblazer in Engineering Fellow by Purdue’s College of Engineering. For additional information, please see: http://www.igorkadota.com.

Abstract: Emerging applications, such as autonomous vehicles and smart factories, increasingly rely on sharing time-sensitive information for monitoring and control. In such application domains, it is essential to keep information fresh, as outdated information loses its value and can lead to system failures and safety risks. The Age-of-Information (AoI) captures the freshness of the information from the perspective of the destination. In this talk, we consider a wireless network with an edge-node receiving time-sensitive information from a number of sensing-nodes through unreliable channels. We formulate a discrete-time decision problem to find a transmission scheduling policy that optimizes the AoI in the network. First, we derive a lower bound on the achievable AoI performance. Then, we develop three low-complexity scheduling policies with performance guarantees: a randomized policy, a Max-Weight policy and a Whittle’s Index policy. Leveraging our theoretical results, we propose WiSwarm: an AoI-based application layer middleware that enables the customization of WiFi networks to the needs of time-sensitive applications. To demonstrate the benefits of WiSwarm in real operating scenarios, we implement a mobility tracking application using a swarm of UAVs communicating with a central controller (i.e., the edge-node) via WiFi.