Energy-Efficient Cluster-based Routing Protocol in Internet of Things Using Swarm Intelligence

Abstract

Energy conservation is a difficult challenge, because the Internet of Things (IoT) connects limited resource devices. Clustering is an efficient method for energy saving in network nodes. The existing clustering algorithms have problems with the short lifespan of a network, an unbalanced load among the network nodes and increased end-to-end delays. This paper proposes a new Cluster Head (CH) selection and cluster formation algorithm to overcome these issues. The process has two phases. First, the CH is selected using a Swarm Intelligence Algorithm called Sailfish optimization Algorithm (SOA). Second, the cluster is formed by the Euclidean distance. The simulation is conducted using the NS2 simulator. The efficacy of the SOA is compared to Improved Ant Bee Colony optimization-based Clustering (IABCOCT), Enhanced Particle Swarm optimization Technique (EPSOCT) and Hierarchical Clustering-based CH Election (HCCHE). The final results of the simulation show that the proposed SOA improves network life and decreases node-to-sink delays.