Analysis of Existing Clustering Algorithms for Wireless Sensor Networks

Abstract

With the recent advancement in MEMS technology, researchers in academics as well as in industry are showing their immense interest in Wireless Sensor Networks (WSNs) since the past decade. WSNs are the networks composed of uniformly or randomly distributed autonomous low-cost nodes used for reliable monitoring of environmental parameters. These resource-constrained sensor nodes work in a synergetic manner to perform a sensing process. Wireless Sensor Networks have a significant role in different areas like habitat monitoring, health monitoring, intelligent and adaptive traffic management, military surveillance, target tracking, aircraft control, forest fire detection, air pollution monitoring, etc. These networks face some critical energy challenges while doing data aggregation, node deployment, localization, and clustering. This chapter presents the analysis of different clustering algorithms proposed so far to lengthen the network lifetime and to increase the network scalability.