Back to Search Start Over

Joint Link Scheduling and Power Allocation in Imperfect and Energy-Constrained Underwater Wireless Sensor Networks

Authors :
Zhang, Tong
Gou, Yu
Liu, Jun
Song, Shanshan
Yang, Tingting
Cui, Jun-Hong
Source :
IEEE Transactions on Mobile Computing; October 2024, Vol. 23 Issue: 10 p9863-9880, 18p
Publication Year :
2024

Abstract

Underwater wireless sensor networks (UWSNs) stand as promising technologies facilitating diverse underwater applications. However, the major design issues of the considered system are the severely limited energy supply and unexpected node malfunctions. This paper aims to provide fair, efficient, and reliable (FER) communication to the imperfect and energy-constrained UWSNs (IC-UWSNs). Therefore, we formulate a FER-communication optimization problem (FERCOP) and propose ICRL-JSA to solve the formulated problem. ICRL-JSA is a deep multi-agent reinforcement learning (MARL)-based optimizer for IC-UWSNs through joint link scheduling and power allocation, which automatically learns scheduling algorithms without human intervention. However, conventional RL methods are unable to address the challenges posed by underwater environments and IC-UWSNs. To construct ICRL-JSA, we integrate deep Q-network into IC-UWSNs and propose an advanced training mechanism to deal with complex acoustic channels, limited energy supplies, and unexpected node malfunctions. Simulation results demonstrate the superiority of the proposed ICRL-JSA scheme with an advanced training mechanism compared to various benchmark algorithms.

Details

Language :
English
ISSN :
15361233
Volume :
23
Issue :
10
Database :
Supplemental Index
Journal :
IEEE Transactions on Mobile Computing
Publication Type :
Periodical
Accession number :
ejs67329065
Full Text :
https://doi.org/10.1109/TMC.2024.3368425