Research on Hierarchical Clustering LEACH Protocol Optimization Algorithm Based on Chebyshev Distance

Abstract

For the problems of premature death of cluster head nodes, short network life cycle and fast energy consumption in hierarchical clustering LEACH protocol in wireless sensor networks, an improved routing protocol K-means LEACH distance optimization algorithm based on LEACH is proposed in this paper. The improved routing algorithm takes into account the problems such as random selection of cluster heads and tedious calculation of distance formula in LEACH algorithm, so K-means clustering algorithm is introduced. The specific scheme is to first divide the data into K classes, then select the appropriate cluster heads, and introduce the Chebyshev distance formula on the basis of K-means clustering algorithm. From the comparative analysis of the simulation results, the K-means LEACH distance optimization algorithm compared to the original LEACH algorithm wireless network node life cycle by 64%, node energy consumption by 26%, which is conducive to improving the stability of WSN, reducing node energy consumption and extending the network survival time.

Optimizing Cluster Head Selection in Mobile Ad Hoc Networks: A Connectivity Probability Approach Using Poisson Distribution and Residual Energy

“…A prominent approach from recent studies involves the hierarchical selection of cluster heads (CHs) to manage node groups and ensure equitable energy dispersion across the network [7][8][9]. These CHs are primarily responsible for data aggregation, managing node transmissions, reducing data redundancies, compressing information, and forwarding the compressed data to either a base station or another CH [10,11]. The Low Energy Adaptive Clustering Hierarchy (LEACH) protocol has emerged as a significant contribution, extensively utilized in mobile Ad Hoc networks [12][13][14].…”