M. Hatami, M. Leinonen, Z. Chen, N. Pappas and M. Codreanu, "On-Demand AoI Minimization in Resource-Constrained Cache-Enabled IoT Networks With Energy Harvesting Sensors," in IEEE Transactions on Communications, vol. 70, no. 11, pp. 7446-7463, Nov. 2022, doi: 10.1109/TCOMM.2022.3208873.
On-demand AoI minimization in resource-constrained cache-enabled IoT networks with energy harvesting sensors
|Author:||Hatami, Mohammad1; Leinonen, Markus1; Chen, Zheng2;|
1Centre for Wireless Communications – Radio Technologies, University of Oulu, 90014 Oulu
2Department of Science and Technology, Linköping University, 58183 Linköping, Sweden
|Online Access:||PDF Full Text (PDF, 2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022101161544
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2022-10-11
We consider a resource-constrained IoT network, where multiple 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 deciding whether to command the corresponding sensor to send a fresh status update or retrieve the most recently received measurement from the cache. Our objective is to find the best actions of the edge node to minimize the average age of information (AoI) of the received measurements upon request, i.e., average on-demand AoI, subject to per-slot transmission and energy constraints. First, we derive a Markov decision process model and propose an iterative algorithm that obtains an optimal policy. Then, we develop an asymptotically optimal low-complexity algorithm — termed relax-then-truncate — and prove that it is optimal as the number of sensors goes to infinity. Simulation results illustrate that the proposed relax-then-truncate approach significantly reduces the average on-demand AoI compared to a request-aware greedy policy and a weighted AoI policy, and also depict that it performs close to the optimal solution even for moderate numbers of sensors.
IEEE transactions on communications
|Pages:||7446 - 7463|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
The work has been financially supported in part by Infotech Oulu, the Academy of Finland (grant 323698), and Academy of Finland 6Genesis Flagship (grant 318927). M. Hatami would like to acknowledge the support of Nokia Foundation. The work of M. Leinonen has also been financially supported in part by the Academy of Finland (grant 340171 and 319485). The work of N. Pappas and Z. Chen have been supported in part by the Swedish Research Council (VR), ELLIIT, and CENIIT. Z. Chen would like to acknowledge the support of Knut and Alice Wallenberg (KAW) Foundation. This article was presented in part at IEEE International Symposium on Information Theory, Espoo, Finland, in 2022.
|Academy of Finland Grant Number:||
323698 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
340171 (Academy of Finland Funding decision)
319485 (Academy of Finland Funding decision)
© 2022 Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/