Comparative Evaluation of Cluster-Head Selection Algorithms for Wireless Sensor Networks

Abstract

The self-organizing wireless sensor networks (WSNs) have become an important research area in the emerging technologies. For several years, these remotely deployed WSNs have laid many unparalleled challenges to the researchers like overall energy efficiency, network lifetime, secure data transmission and aggregation of the collected data. Depending on the network orientation, WSN may either have a flat architecture or a clustered architecture. Over the years, clustering has become an essential research area as clustered WSN has been observed to have an advantage of several features like better lifetime, energy efficiency and throughput over flat WSN. Clustering has become an efficient criterion for a better data transmission through the network using relevant cluster-head selection algorithms. The prime objective of this paper is to survey and evaluate several cluster-head selection algorithms on various clustering strategies. Based on these clustering strategies, comparison of the clustering algorithms has been done.