Asymptotically optimal on-demand AoI minimization in energy harvesting IoT networks
Hatami, Mohammad; Leinonen, Markus; Chen, Zheng; Pappas, Nikolaos; Codreanu, Marian (2022-08-03)
M. Hatami, M. Leinonen, Z. Chen, N. Pappas and M. Codreanu, "Asymptotically Optimal On-Demand AoI Minimization in Energy Harvesting IoT Networks," 2022 IEEE International Symposium on Information Theory (ISIT), 2022, pp. 922-927, doi: 10.1109/ISIT50566.2022.9834773.
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
https://rightsstatements.org/vocab/InC/1.0/
https://urn.fi/URN:NBN:fi-fe2022101161550
Tiivistelmä
Abstract
We consider a resource-constrained IoT network, where users make on-demand requests to a cache-enabled edge node to send status updates about various random processes, each monitored by an energy harvesting sensor. The edge node serves users’ requests by either commanding the corresponding sensor to send a fresh status update or retrieving the most recently received measurement from the cache. We aim to find a control policy at the edge node to minimize the average age of information (AoI) of the received measurements upon requests, i.e., average on-demand AoI, subject to per-slot transmission and energy constraints. We develop a low-complexity algorithm — termed relax-then-truncate — and prove that it is asymptotically optimal as the number of sensors goes to infinity. Numerical results assess the performance of the proposed method.
Kokoelmat
- Avoin saatavuus [38865]