A review of energy-efficient clustering and routing techniques in wireless sensor networks: Key metrics and future trend

Abstract

Wireless Sensor Networks (WSNs) have become a cornerstone of modern technology, especially in applications like the Internet of Things (IoT), where they provide scalable and effective solutions for communication and monitoring applications. However, the finite energy of sensor nodes introduces a significant challenge, as it directly influences the network's lifespan and reliability. Routing protocols and clustering solutions have emerged as ideal ways to address these energy concerns. By forming sensors into clusters and enhancing data transmission routes, these protocols reduce energy consumption and improve network efficiency. Modern approaches incorporate techniques such as metaheuristics, fuzzy logic, and machine learning to address issues like load balancing, node mobility, and network topology changes. Despite considerable progress, gaps remain in scalability, Quality of Service (QoS) integration, and the adaptability of clustering protocols for dynamic environments. This research reviews the state of the art in optimizing energy efficiency in Wireless Sensor Networks. It addresses routing approaches and clustering solutions and highlights performance and quality key metrics and future trends.