University of Oulu

M. Hatami, M. Leinonen and M. Codreanu, "Minimizing Average On-Demand AoI in an IoT Network with Energy Harvesting Sensors," 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2021, pp. 1-5, doi: 10.1109/SPAWC51858.2021.9593235

Minimizing average on-demand AoI in an IoT network with energy harvesting sensors

Saved in:
Author: Hatami, Mohammad1; Leinonen, Markus1; Codreanu, Marian2
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
2Department of Science and Technology, Linkoping University, Sweden
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202201209512
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2022-01-20
Description:

Abstract

Delivering timely status information of a random process has become increasingly important for time-sensitive applications, e.g., vehicle tracking and environment monitoring. We consider an IoT sensing network, where a cache-enabled wireless edge node receives on-demand requests from multiple users to send status updates on physical quantities, each measured by an energy harvesting sensor. To serve users’ requests, the edge node uses the current information state (i.e., the number of requests, battery level, and AoI for each sensor) to decide whether to command a sensor to send a status update or to retrieve the most recently received sensor’s measurements from the cache. We aim at finding the best actions of the edge node to minimize the average AoI of the served measurements at the users, i.e., average on-demand AoI. We model this as a Markov decision process problem and derive a relative value iteration algorithm to find an optimal policy. Simulation results illustrate the threshold-based structure of an optimal policy and show that the proposed on-demand updating policy outperforms the greedy (myopic) policy and also, by accounting for the per-sensor request frequencies and intensities, the pure average AoI minimization policy that keeps the edge node updated regardless of requests.

see all

Series: IEEE International Workshop on Signal Processing Advances in Wireless Communications
ISSN: 2325-3789
ISSN-L: 2325-3789
ISBN: 978-1-6654-2851-4
ISBN Print: 978-1-6654-2852-1
Article number: 9593235
DOI: 10.1109/SPAWC51858.2021.9593235
OADOI: https://oadoi.org/10.1109/SPAWC51858.2021.9593235
Host publication: 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Conference: IEEE International Workshop on Signal Processing Advances in Wireless Communications
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research has been financially supported by the Infotech Oulu, the Academy of Finland (grant 323698), and Academy of Finland 6Genesis Flagship (grant 318927). The work of M. Leinonen has also been financially supported in part by the Academy of Finland (grant 319485). M. Hatami would like to acknowledge the support of HPY Research Foundation and Riitta ja Jorma J. Takanen Foundation.
Academy of Finland Grant Number: 323698
318927
319485
Detailed Information: 323698 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
319485 (Academy of Finland Funding decision)
Copyright information: © 2021 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.