Energy Efficient Structure-Free Data Aggregation and Delivery in WSN: A Design Thinking Approach

The Wireless Sensor Network's (WSN) efficient communication capabilities, it has found a wide range of applications, some of which include battlefield surveillance, monitoring of surroundings and congestion, and contemporary agriculture. The energy use of certain sensor nodes inside a WSN, the delivery of packets, the amount of delay, and the lifetime of the network are all limited. In previous work, energy efficient is not achieved effectively in sensor network. The Enhanced Squirrel Search Algorithm (ESSA) is suggested in this study to address the problem by enhancing data aggregation and network energy efficiency. Data aggregation is carried out via Cluster Heads (CH), and CH based data aggregation is a crucial approach for lowering each sensor node's energy usage in WSN. In order to increase the network lifespan over WSN, CH selection is crucial. Using an objective function that chooses the best CH sensor node to gather data, the ESSA produces the best fitness values. The selection of sensor nodes takes into account factors like energy, distance, and bandwidth. The suggested ESSA model's results are simulated using energy consumption, network lifespan, data aggregation accuracy, and time. Based on the experimental findings and observations, the suggested ESSA model extends the life of the network and increases data aggregation accuracy while using less energy.