An Energy Efficient Improved Clustering based Data Compression Protocol in Wireless Sensor Network

Extensive research methodologies have revealed that wireless sensor networks (WSNs) are being utilized across a diverse array of applications, facilitating wireless data collection, communication, and intelligent computing. Sensor nodes (SNs) are compact in size, battery-powered and they are incorporated with intelligent computing capabilities to detect changes in the physical environment. These SNs convert sensed data into digital format and transmit it to a central data collection node. Nevertheless, SNs face resource limitations and rely on finite battery power. On the other hand, continuous monitoring of the physical environment consumes significant energy, leading to rapid battery depletion and potential node failure. Therefore, energy preservation in WSNs is regarded as a paramount concern to sustain node functionality over extended durations. In this research paper, we proposed a model that employs a Compressive sensing (CS) in WSN which optimizes transmission rates and distributes traffic load evenly in the network. Moreover, Cluster-based strategies are also incorporated with CS for overall network energy efficiency and to effectively extend the lifespan of the network. This approach has resulted in the development of an energyefficient clustering protocol, referred to as the An Energy Efficient Improved Clustering-Based Data Compression Protocol (EEIC-DCP), proposed specifically for WSNs. Extensive simulations have validated that our proposed approach significantly improves energy conservation and prolongs the network’s operational lifespan.