A novel routing protocol based on grey wolf optimization and Q learning for wireless body area network

作者：

Highlights：

• The paper is dedicated to proposed a cluster-based routing protocol for WBAN.

• The paper utilizes the benefits of machine learning.

• A novel approach, MGWOQL, is proposed for cluster head selection and updation.

• The multi-objective function is designed to select the optimal cluster head node.

• The result shows better network longevity, residual energy, and path loss.

摘要

•The paper is dedicated to proposed a cluster-based routing protocol for WBAN.•The paper utilizes the benefits of machine learning.•A novel approach, MGWOQL, is proposed for cluster head selection and updation.•The multi-objective function is designed to select the optimal cluster head node.•The result shows better network longevity, residual energy, and path loss.

论文关键词：Wireless Body Area Network (WBAN),Machine Learning,Optimization,Q-Learning,Energy Efficiency,Grey wolf optimizer

论文评审过程：Received 2 November 2021, Revised 10 June 2022, Accepted 6 August 2022, Available online 11 August 2022, Version of Record 13 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118477