A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network

Abstract

Wireless sensor network consists of hundreds to thousands of sensor nodes gathering various data including temperature, sound, location, etc. They have been applied to numerous fields such as healthcare, monitoring system, military, and so forth. It is usually difficult to recharge or replace the sensor nodes which have limited battery capacity. Energy efficiency is thus a primary issue in maintaining the network. In this paper we propose an efficient cluster head selection method using K-means algorithm to maximize the energy efficiency of wireless sensor network. It is based on the concept of finding the cluster head minimizing the sum of Euclidean distances between the head and member nodes. Computer simulation shows that the proposed approach allows better performance than the existing hierarchical routing protocols such as LEACH and HEED in terms of network lifetime.