Enhanced Data Aggregation Based on Optimise Crow Search Featured Hybrid Salp Swarm Optimization to Improve the Routing Communication

Wireless Sensor Networks (WSNs) are increasingly vital for enabling enhanced communication globally. A significant challenge in Multi-Agent (MA) communication within these networks is minimizing communication delay through efficient routing. WSN is the development of advanced communication systems. Lack of communication and finding delay-aware routing are significant problems in Multi-Agent (MA) communication. To address the issue, we propose Enhanced Data Aggregation (EDA) based on optimised Crow Search featured Hybrid Salp Swarm Optimization (CSF-HSSO) to improve routing communication. The K-means clustering is utilized to optimize the sensor node to form a structured relative source network. According to the cluster nodes, the Improved Crow Search Algorithm (ICSA) is applied to select the feature-dependent routing from the Cluster Head (CH). Finally, the HSSO creates a Route Planning (RP) to choose the optimal routing. The proposed method achieves efficient path selection, thereby improving network lifetime, packet delivery ratio, and throughput.