Optimizing Super Cluster Head Selection in Leach Using Type-2 Fuzzy Logic

Abstract

With the advancements in technology, the communication networks have also shifted to wireless networks from wired networks. Wireless Sensor Networks (WSNs) is a wireless network that is growing manifold. It is a widely accepted wireless mean of communication of the current generation. WSNs have been proved to be cost effective networks as they save energy and indirectly reduce the maintenance cost, and hence enhances the lifetime of the network. In order to make an energy efficient network, numerous routing protocols have been proposed. But out of these, clustering approaches have gained significant interest, due to their efficient selection process of the cluster head (CH) and aggregation of data. LEACH is the foremost clustering approach and has proven to be quite effective as compared to other protocols. Clustering approaches are known for balancing various key factors that affect the overall operation of WSNs. Clustering guarantees increased stability, less load as all nodes send data to the CH instead of direct communication to Base Station (BS), is more robust in nature as it can cope up to various network changes and ensures load balancing which prolongs the network lifetime. In this work, an energy efficient Super Cluster Head (SCH) selection approach by enhancing the traditional LEACH protocol is proposed. The approach has considered the distance between the SCH and BS along with remaining battery and centrality. The Type-2 Fuzzy inference system is applied for optimizing the SCH selection. The results prove that the proposed LEACH – Type-2 Fuzzy approach is proficient than the traditional LEACH - Fuzzy approach in terms of network lifetime, number of dead nodes and alive nodes.