A Review On IOT Wireless Network Optimization Models And Techniques

Wireless Sensor Networks (WSNs) and Internet of Things (IoT) systems play a crucial role in modern smart applications such as smart cities, healthcare, industrial automation, and precision agriculture. Despite rapid advances in communication, cloud, and edge computing technologies, energy efficiency remains a fundamental challenge due to the limited power resources of sensor nodes. This survey presents a comprehensive review of energy losses in WSN-based IoT networks and systematically analyzes state-of-the-art optimization techniques aimed at prolonging network operation. The paper discusses architectural aspects of WSNs, sources of energy waste, and major optimization strategies, including radio optimization, data reduction, sleep/wakeup scheduling, and energy-aware routing. Furthermore, recent approaches based on metaheuristic optimization, swarm intelligence, and machine learning are reviewed and compared. By organizing existing methods into a unified taxonomy, this survey highlights current research trends, practical design trade-offs, and open challenges, thereby providing useful guidelines for developing scalable, energy-efficient, and reliable WSN-IoT systems.