Minimizing Age of Information for Real-Time Monitoring in
Resource-Constrained Industrial IoT Networks
报告人: 陈赫博士(Dr He Henry Chen), 香港中文大学 (The Chinese University of Hong Kong)
Abstract: In this talk, we consider an Industrial Internet of Thing (IIoT) system with a source monitoring a dynamic process with randomly generated status updates. The status updates are sent to a designated destination in a real-time manner over an unreliable link. The source is subject to a practical constraint of limited average transmission power. Thus, the system should carefully schedule when to transmit a fresh status update or retransmit the stale one. To characterize the performance of timely status update, we adopt a recent concept, Age of Information (AoI), as the performance metric. We aim to minimize the long-term average AoI under the limited average transmission power at the source, by formulating a constrained Markov Decision Process (CMDP) problem. To address the formulated CMDP, we recast it into an unconstrained Markov Decision Process (MDP) through Lagrangian relaxation. We prove the existence of optimal stationary policy of the original CMDP, which is a randomized mixture of two deterministic stationary policies of the unconstrained MDP. We also explore the characteristics of the problem to reduce the action space of each state to significantly reduce the computation complexity. We further prove the threshold structure of the optimal deterministic policy for the unconstrained MDP.
Short Bio: Dr. He (Henry) CHEN received the B.Eng. degree in Communication Engineering and the M.Eng. degree in Communication and Information Systems from Shandong University, Jinan, China, in 2008 and 2011, respectively, and the Ph.D. degree in Electrical Engineering from The University of Sydney, Sydney, Australia, in 2015. He was a Research Fellow with the School of Electrical and Information Engineering, The University of Sydney before he joined Department of Information Engineering at the Chinese University of Hong Kong as a faculty member, where he is now a Research Assistant Professor.
Dr. Chen’s current research interests are in the field of Internet of Things, with a particular focus on ultrareliable low-latency wireless for industrial IoT, time-sensitive networking (TSN), timely status update in real-time monitoring, and IoT network security. He has published more than 100 technical papers in refereed international journals and conferences. Dr. Chen received the Outstanding Bachelor Thesis of Shandong University, the Outstanding Master Thesis of Shandong Province, the Chinese Government Award for Outstanding Self-Financed Students Abroad, and a best paper award from IEEE WCNC 2018.