Energy and Security Aware Clustering in Internet of Things with Improved SandPiper Optimization Model

Abstract Internet of Things (IoT) is a networking paradigm shift that aims to link almost everything on the world. Due to the limited form of smart devices, energy-efficient routing would be critical to their effective implementation. Clustering techniques divide a network's nodes into groups or clusters, each of which is led by a specified node known as the cluster head. Clustering methods have been presented in the area of Wireless Sensor Networks (WSN), while their application in IoT might solve comparable problems. By transferring a major portion of communication overhead to the cluster head, clustering would promote topology maintenance and energy efficient routing. Therefore, this article aims to establish a novel clustering model in IoT, in which the cluster head selection is performed via a proposed Sandpiper Optimization with Cycle Crossover Process (SOCCP) model. Moreover, this cluster head selection includes certain constraints including (i) Distance (ii) Energy (iii) security (based on the risk levels), and (iv) Cluster Radius, respectively. At first, the clustering is done by the Optimized Fuzzy C-Means (FCM) algorithm. Here, the determination of the cluster head and cluster radius is tuned optimally via an adopted SOCCP model. At the end, the results of the adopted technique are computed to extant based on various metrics including alive node analysis, risk analysis, distance analysis, cluster radius analysis, as well as normalized energy analysis, respectively.