Enhancement of LEACH Based on K-means Algorithm and Stochastic Optimization

Abstract

In Wireless Sensor Networks (WSNs), maximizing the life of the Sensor Nodes (SNs), and energy conservation measures are essential to enhance the performance of the WSNs. A Low-Energy Adaptive Clustering Hierarchy (LEACH) routing protocol has been proposed specifically for WSNs to increase the network lifetime. However, in LEACH protocol the criteria for clustering and selecting Cluster Heads (CHs) nodes were not mentioned. Accordingly, researchers have been focusing on ways to strengthen the LEACH algorithm to make it more efficient. In this paper, we propose to improve the LEACH protocol by combining the use of K-means algorithm for clustering and Slime Mould Algorithm (SMA), a new stochastic optimization to select nodes as CHs. The proposed routing algorithm, called SMA-LEACH, is superior to other algorithms, namely PSO-LEACH, BA-LEACH, which using Particle Swarm Optimization (PSO), Bat Algorithm (BA) to improve LEACH, respectively. Simulation analysis shows that the SMA-LEACH obviously reduces network energy consumption and extends the lifetime of WSNs.