Hybrid optimization algorithm for security aware cluster head selection process to aid hierarchical routing in wireless sensor network

In wireless sensor networks, clustering is said to be the most noteworthy technique for increasing the lifetime of network that directly leads a better routing mechanism. This approach involves grouping of sensor nodes to clusters and choosing the appropriate cluster heads for each cluster. In fact, cluster heads gathers data from corresponding nodes in cluster and transmits those aggregated data to base station. However, the major issue in this is the selection of the appropriate cluster head. Till now, many research works have been carried out for solving this issue by considering different constraints. This paper introduces a new cluster‐based routing model by selecting the optimal cluster head. Moreover, a novel algorithm known as grey wolf updated whale optimization algorithm is introduced. Here, a new multi‐objective function is defined with respect to different constraints like distance, delay, security and energy, respectively. Finally, the performance of security aware clustering with grey wolf updated whale optimization algorithm is evaluated and validated over other conventional works with respect to alive node analysis, throughput and normalized network energy, respectively.

Abstract licence: CC BY-ND

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