EEM-CRP: Energy-Efficient Meta-Heuristic Cluster-Based Routing Protocol for WSNs

Wireless sensor network (WSN) is an infrastructure-less network that deploys many interconnected sensors to monitor physical environmental conditions and sends data to the cloud/base station. Sensors monitor, analyze, and route data in Internet of Things (IoT)/WSNs. Nodes consume maximum energy for processing and routing the data from the physical environment. This article proposes an energy-efficient meta-heuristic cluster-based routing protocol (EEM-CRP) for WSNs to address energy issues. EEM-CRP protocol exploits dragonfly meta-heuristic algorithm for selecting optimal cluster head (CH) and route. The dragonfly algorithm (DA) is a kind of decision-making approach (DMA) where it works for exploitation and exploration. DA-based EEM-CRP protocol is divided into two parts: 1) optimal cluster head selection (OCHS) and 2) optimal route selection (ORS). OCHS is based on the exploitation aspect of DA and it selects the CH based on parameters such as node density, residual energy, and distance. ORS is based on exploration and choosing an optimal path based on the random walk/levy distribution function. It covers a large region with reduced energy consumption and overcomes network overhead issues. EEM-CRP ensures the participation of the maximum number of active sensor nodes’ inflow of data without much or no delay. EEM-CRP performance is compared with LEACH, whale and gray wolves (WGWO), and hybridization of metaheuristic algorithm for dynamic cluster-based routing protocol (HMBCR) algorithms on important factors including packet delivery ratio (PDR), delay, number of active nodes, and average residual energy (ARE). According to the simulation results, the EEM-CRP significantly exceeds the methodologies used by its rivals in terms of energy efficiency.