Research on Unequal Clustering Protocol based on Fuzzy Logic and Entropy Weight Method

Abstract

Clustering is an effective strategy to minimize the energy consumption of nodes in energy-constrained wireless sensor networks. In clustered wireless sensor networks, the network is divided into multiple clusters, and each cluster has a coordinator called cluster head, which collects data from its cluster members and forwards it to the base station through other cluster heads. Cluster wireless sensor networks often have hot spot problems. Due to high energy consumption caused by data forwarding load, cluster heads near the base station die earlier. This kind of node death leads to the coverage loophole of the network early and reduces the life cycle of the network. Unequal clustering is a technology to solve this problem. In non-uniform clustering wireless sensor networks, the size of clusters near the base station is smaller than that far away from the base station. In the process of cluster formation, non-cluster-head nodes are generally added to nearby cluster-head nodes. In this paper, an unequal clustering protocol based on fuzzy logic and entropy weight method (FEUC) is proposed to extend the life cycle of the network. This protocol makes the network form clusters of different sizes. Fuzzy logic method is used to select cluster heads and non-cluster heads join cluster heads to form clusters. The objective entropy weight method is used to select relay cluster heads to implement multi-hop routing strategy. Mamdani method is used for fuzzy reasoning. The proposed protocol is compared with the low-energy adaptive clustering hierarchy (LEACH) protocol, the energy-aware unequal clustering fuzzy protocol (EAUCF), and the fuzzy-based unequal clustering protocol (FUCA), in all scenarios, the proposed protocol has better performance.