Abstract
Clustering is considered to be the most significant method for resolving conflicts of data transmission and maximizing the life span of the network in Wireless Sensor Networks (WSNs). The sensor nodes are densely deployed to satisfy the coverage requirement; this causes some nodes to lazy mode. Some algorithms of cluster heads (CHs) selection were already proposed for sufficient energy management. However, it remains as a challenging task in WSN due to network scalability, protocol characteristics, and data transfer rate. This paper aims to propose a novel clustering model is proposed by this research work for cluster head selection (CHS) that considers four primary constraints: namely energy consumption, delay, distance, and security. In addition, for optimal selection of CH, a novel algorithm, which is the hybridization of the Dragon Fly (DA) algorithm and firefly algorithm, is proposed. The proposed hybrid algorithm is named as FireFly replaced Position Update in Dragonfly (FPU-DA). The performance of the proposed work is compared with conventional algorithms. Subsequently, a parametric analysis is performed by varying the weight factor of the proposed FPU-DA model to investigate its impact on the performance of the CHS problem. The proposed FPU-DA model at round 2000 shows 9%, better than KNN and SOM. Thus, the analysis results proved that the proposed model attains a better life span when compared to that of other conventional models.