Energy efficient multi-objective cluster-based routing protocol for WSN using Interval Type-2 Fuzzy Logic modified dingo optimization

Abstract

In the design of Wireless sensor networks (WSNs), maximizing network lifetime and sustaining energy stability is identified as the challenging problem since it comprises of compact sized and energy limited sensor nodes that cooperates during data routing. The existing clustering-based routing mechanisms accomplished energy efficiency and attempted to minimize the distance between the cluster head (CH) and the sink node for network lifetime improvement. The adoption of swarm intelligence algorithms and fuzzy logic is determined to the ideal computational intelligence techniques which are suitable for NP-hard problem like the multi-hop route selection process. In this paper, A Modified Dingo Optimization Algorithm-based Clustering Mechanism (MDOACM) is proposed for addressing the limitations of the clustering protocol with respect to cluster head (CH) lifetime and cluster quality. This MDOACM-based clustering protocol utilized Interval Type-2 Fuzzy Logic (IT2FL) for determining the trust level of each sensor node since the existence of an untrustworthy node introduces adverse impact on the data quality and reliability. It specifically used MDOA for achieving better clustering with balanced trade-off between the rate of exploration and exploitation such that frequent re-clustering is prevented. It effectively prevented malicious nodes with minimized energy consumption and enhanced network lifetime. It also adopted a communication system that supports the sensors in attaining the objective with reduced energy and maximized confidence level during the transmission of full exploration data. The results of MDOACM confirmed an average improvement in network lifetime of 23.18% and 25.16% with respect to different energy levels and density of sensor nodes.