Design of an Energy-Efficient Routing Protocol Using Adaptive PSO Technique in Wireless Sensor Networks

Demand of wireless sensor networks has increased dramatically due to their significant use in various real-time industrial, military, and medical field applications. Due to their vast applications, WSNs have become an attractive field of research. These sensor networks are easy to deploy and can efficiently monitor the area and environment, but due to limited resources, such as memory, battery capacity, and computation capacity, it becomes a challenging task. In this work, we focus on the network lifetime enhancement by developing particle swarm optimization (PSO)-based technique. In order to achieve the desired performance, the complete proposed model is divided into various stages where first of all, sensor nodes are deployed randomly. Later, cluster head selection is performed followed by the shortest path identification. In order to minimize the energy consumption, we apply multi-objective PSO scheme. However, fitness function computation suffers from the slow convergence which leads to the premature solution resulting in degraded communication performance. In order to address this issue, we present a new fitness function computation which considers residual energy parameter and formulates a new energy consumption model for each node which helps to optimize the power consumption during data transmission and reception by considering the sleeping phases of sensor nodes. An extensive simulation study is carried out using MATLAB simulation tool, and the performance of the proposed approach is compared with the state-of-the-art techniques. Results and discussion of this approach show that the proposed approach can achieve better performance in terms of QoS, packet delivery rate, and network lifetime enhancement.