Joint Data Gathering and Energy Efficient Wireless Sensor Node Charging Based on Coati Optimization in Wireless Sensor Networks

Wireless sensor networks (WSNs) consist of numerous autonomous sensor nodes distributed across a physical environment to monitor various occurrences. A key challenge in WSNs is ensuring efficient data collection and energy replenishment of sensor nodes. While several strategies exist to integrate mobile data collection with node recharging, many face limitations in scalability, energy efficiency, or latency. This proposed approach that combines data collection and sensor node charging is based on coati optimization. Initially, sensor nodes are uniformly deployed across the sensing area, with equal transmission ranges and energy capacities. The region is divided into grids, and grid coordinates are selected within each grid using a weight function that considers both the remaining energy of sensors and their average distance from neighboring nodes. To prevent node energy depletion, two mobile chargers (MCs) are simultaneously dispatched along optimized routes derived through coati optimization. After each service round, the MCs return to the sink to transmit collected data and recharge. Experimental results demonstrate that the proposed method achieves a 31% reduction in packet delay, a 0.023% bit error rate, 6.2% energy consumption, and a 42% signal-to-noise ratio, highlighting its effectiveness in enhancing WSN performance. Thus, coati optimization proves to be a promising strategy for efficient data collection and sensor node charging.