Open AccessEnhancement of LEACH Based on K-means Algorithm and Stochastic Optimization
Author(s) -
Tuyen Nguyen Viet,
Trang Pham Thi Quynh,
Hang Duong Thi
Publication year - 2021
Publication title -
journal of communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.185
H-Index - 35
eISSN - 2374-4367
pISSN - 1796-2021
DOI - 10.12720/jcm.16.9.406-410
Subject(s) - cluster analysis , computer science , wireless sensor network , particle swarm optimization , routing protocol , energy consumption , sma* , protocol (science) , algorithm , mathematical optimization , routing (electronic design automation) , computer network , distributed computing , mathematics , engineering , artificial intelligence , medicine , alternative medicine , pathology , electrical engineering
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.