Energy Efficient Routing by Using Nature Inspired Methods for Internet of Everything (IoE) Network

Abstract

Wireless Sensor Network (WSN) is a cutting-edge strategy and technology where sensor nodes gather information about the physical environment and the areas through single-hop or multi-hop data communication to the Sink Node (SN). Complex routing procedures may exhaust the energy reserves of the sensor nodes due to the restricted computing power and battery resources. Load balancing is rarely taken into account by routing protocols when choosing an efficient routing path. This study proposes a Spider Monkey Optimization using Unequal Size Clusters (SMOUSC) protocol which is ideal for time-sensitive applications like telematics, logistics, and disaster assistance. The proposed protocol uses Spider Monkey Optimization (SMO) algorithm by using unequal size clusters to maximize energy efficiency while taking into account several variables, such as reduced energy consumption, node residual energy, distance from the Cluster Head (CH), and distance between consecutive CHs, and minimal scheduling delay. By using an unequal size cluster and the smaller size of the cluster that is near the Base Station (BS), CHs save energy by using an SMO approach, CHs store energy. Additionally, dual-hop communication is used to balance the load more effectively and save energy on the remote CHs. The experimental results indicated the better performance of the proposed protocol with less energy consumption and enhance network lifetime as compared to the state-of-the-art protocols.