Fuzzy-based cluster head election mechanisms for wireless sensor networks: A review

Abstract

Cluster head election is considered as the significant entity necessary for prolonging the lifetime of the Wireless Sensor Networks (WSNs). A variety of cluster head election techniques are contributed by a number of researchers to the literature for optimal and effective cluster head election. The cluster head election mechanisms are categorized into random, probabilistic, game theory-based and fuzzy-based schemes. Fuzzy –logic based cluster election techniques are found to be predominant than the exiting approaches as they facilitate the option of electing and optimizing the cluster heads at each round of data transmission. The incorporation of fuzzy inference engine that elucidates potential input parameters like interdistance between cluster heads, interdistance between cluster members, residual energy threshold and drain rate of sensor nodes make it highly suitable in framing if-then rules. The performance improvements enabled by the existing fuzzy logic inspired cluster head election schemes are also portrayed. Finally, the pros and cons of the reviewed Fuzzy based cluster head lection schemes are presented with the specific highlight on the performance metrics used for proving its superiority.