Designing Cluster-Based Optimal Data Gathering Routing Protocol for Wireless Sensor Networks with Mobile Sink

Abstract

Wireless sensor nodes are battery-powered nodes that detect and gather data in areas where there are no opportunities for charging batteries. They use the majority of their battery to send data to the sink (base station) for any purpose. As a result, we must consider sensor node energy consumption as a crucial component in extending the Wireless Sensor Network (WSN) lifetime. Another major consideration in WSN is the mobility issue. Because it is difficult for a mobile sink to visit each sensor node, scheduling the mobile sink is a focused issue. Rather than visiting all of the sensor nodes, the mobile sink gathers data from the Cluster-head (CH). The data is sent to CH by other sensor nodes. The existing works centralized mobile Low-Energy Adaptive Clustering Hierarchy (LEACH-CM) and centralized distributed Low Energy Adaptive Cluster Hierarchy (LEACH-CDM) provide several benefits in terms of reducing energy consumption and increasing the amount of data received by the base station (BS). However, the degradation of network performances in terms of the amount of data received by BS caused by packet loss due to non recognition of the BS position, the trajectory design of the mobile sink (MS), and the in efficient energy. To overcome this problem, we have proposed cluster-based optimal data gathering routing protocols with mobile sink design (COMSD). The proposed COMSD was select an efficient CH based on node density, energy consumption rate, inter-cluster distance, residual energy; optimal data gathered based on CH energy, path length, and cluster size with mobile sink by using particle swarm optimization (PSO) to overcome the problem. The implementation of our work COMSD is simulated by using the MATLAB2021a tool. The performances of the proposed works have evaluated by using throughput, the number of alive and dead nodes, and the network's remaining energy. The proposed work was compared with the two existing LEACH-CM and LEACH-CDM. So, the simulation results indicated that the COMSD improves the alive nodes by 44.08% over LEACH-CM and by 33.8% over LEACH-CDM, throughput by 38.01% over LEACH-CM and by 13.03% over LEACH-CDM, and the network remaining energy by 40.6% over LEACH-CM and by 27% over LEACH-CDM. Therefore, this study concludes that COMSD indicates a better improvement in all performance metrics that shows efficient results over existing works.