Gray Wolf Optimization Algorithm to Enhance Data Aggregation in Wireless Sensor Network
Sathyapriya Loganathan, B. Victoria Jancee, Rajagopalan Senkamalavalli, T. C. Subbu Lakshmi · 2023
Wireless sensor networks (WSNs) have become increasingly popular as distributed systems using small, lightweight nodes with limited resources for monitoring environmental conditions or measuring physical parameters. To minimize energy utilization, data aggregation can be employed to reduce the data quantity forward to the base station (BS). To solve these issues, a Gray wolf optimization algorithm (GWOA) is proposed to enhance data aggregation in WSN. Increasing the network lifetime, node reliability, and throughput with the selection of best cluster heads (CHs) utilizing the Gray Wolf Optimization (GWO) algorithm is the major objective of this research. This approach selects the CH by applying the GWO algorithm established on the node remaining energy, available bandwidth, and distance. The GWO-based clustering protocol minimizes dead nodes and energy utilization and raises the clustering rounds and throughput. The simulation results demonstrate that the increases the node reliability and network throughput.