Smart Sensor Networks: Review of Clustering and Optimization Techniques

Wireless Sensor Networks (WSNs) are built from a large number of autonomous nodes having sensors, wireless connection, CPU, memory, and energy. Because WSNs are so prevalent, there is growing interest in making them smart and autonomous, allowing for applications in smart grids, health care, buildings, and industrial processes. However, they lack a thorough understanding of analytical and computational methodologies, as well as best practices, for building WSN resource allocation schemes, power-efficient protocols, and self-organizing algorithms. We explore energy-efficient clustering and optimization strategies in this study.