An Energy-Efficient Ant-Based Routing Algorithm for Wireless Sensor Networks Using Compressive Sensing

Wireless Sensor Networks (WSNs), a vital component of the Internet of Things (IoT), play an essential role in applications like environmental monitoring, smart homes, and industrial automation. For resource-limited WSNs, an effective data collection method can significantly reduce energy consumption and extend network life. Compressive sensing technology offers an efficient sampling method, significantly reducing data transmission volume in the network and allowing for original data restoration under certain noise levels. This is considered a promising approach. The core contribution of this paper is the development of an energy-efficient routing algorithm for WSNs, combining the principles of compressive sensing and ant colony algorithms. This novel algorithm reimagines data aggregation in clustered networks through compressive sensing, altering the paradigm of traditional intra-cluster communication. It introduces a novel intra-cluster routing optimization method and redesigns the ant colony algorithm to facilitate this optimization. Simulation results show that the proposed EARCS method significantly reduces overall network energy consumption and markedly extends network life compared to traditional methods.