An Energy-Efficient Adaptive Mayfly Optimization Algorithm Based Optimal Routing in Wireless Sensor Network for Military Application

The military administrations and applications cover enormous acres of land of regions. It incorporates arms, ammo weapons, devices, and secretes information. Countless fighters are present at the borders and aggressive locales to protect the regular citizen individuals and improve their security to them. However, some surveillance mechanisms based on modern electronics and technology are required to alert soldiers and military officers immediately in the event of any emergency. Thus, they can make immediate arrangements to increase security and tighten forces. Due to this reason, nowadays, wireless sensors are placed in the area to monitor the information from the border. This will help the soldiers to alert if any emergency happens at the border. One of the main issues of WSN is the limited energy of sensor nodes and high energy consumption. To avoid the problem, in this paper, energy-efficient routing in WSN is proposed. The proposed approach consists of three stages namely, Cluster formation and optimal path-based routing. The clusters are formed using energy function and distance formula. After the cluster formation, the optimal path is selected using an adaptive mayfly optimization algorithm (AMOA). The presentedapproach is implemented by NS2 simulator and performances are compared with existing methods such as Particle swarm optimization (PSO), Mayfly optimization algorithm (MOA), and genetic algorithm (GA) respectively. The performance of presented approach is evaluated based on different metrics.