Balanced Distribution Strategy for the Number of Recharging Requests Based on Dynamic Dual Thresholds in WRSNs
Xiaojie Bian, Chao Sha, Reza Malekian, Chuanxin Zhao, Ruchuan Wang · IEEE Internet of Things Journal · 2024
“Request Triggered Recharging” has been a flexible type of scheduling schemes to allow the mobile charging vehicle (MCV) to supply energy for sensor nodes on demand. However, in most existing works, MCV always passively waits for the arrival of the unpredictable requests that may cause it missing the best departure time to serve nodes. To solve this problem, we propose a balanced distribution strategy for the number of recharging requests based on dynamic dual thresholds (BDRR). First, the adjustable double recharging request thresholds (DRRTs) are set for each node to ensure that all the requesting nodes can be successfully charged. Then, the method for setting the energy replenishment value (MSERV) is proposed to enable the distribution of the moments at which nodes send out their recharging requests being concentrated within each period. Furthermore, an efficient traversal path for the MCV is constructed by safe or dangerous scheduling strategy, and the charging capacity reduction scheme (CCRS) is also executed to help survive more nodes in need. Finally, a passer-by recharging scheme (PRS) is introduced to further improve the energy efficiency (EE) of the MCV. Simulation results show that BDRR outperforms the compared algorithms in terms of surviving rate of sensors as well as the EE of MCV with different network scales.