Fuzzy cluster-based multi-node charging strategy in mobile sensor networks

Abstract

Energy is crucial for the continuous operation of rechargeable sensor networks, and efficient energy replenishment strategies are vital for improving network performance. However, existing solutions primarily focus on stationary sensor networks, and there are fewer strategies for energy replenishment in mobile networks. Typically, a Mobile Car (MC) charges individual mobile nodes one to one. To address the mobility of sensor nodes and enhance the energy replenishment efficiency of the network, this paper proposes a fuzzy clustering-based multi-node charging strategy (MMCS) in Mobile Sensor Network (MSN). Firstly, an improved multi-factor fuzzy C-mean clustering algorithm (MFCM++) is designed to cluster nodes with similar moving directions and remaining energy. Secondly, the cuckoo search algorithm (CS) is utilized to determine the optimal charging position for each cluster based on the varying energy demand levels of mobile nodes, thereby reducing the cluster charging waiting time. Finally, a spatio-temporal factor-based cluster selection algorithm (STCS) is developed to determine the order of cluster charging and select the next cluster to be charged. Extensive simulation results demonstrate that MMCS effectively enhances network performance, reduces energy costs, and addresses the energy problem in large-scale MSNs