DefinePK

Abstract

The Internet of Things network depends heavily on wireless sensor networks because they make it possible for dispersed sensor nodes to efficiently gather and transmit data to centralized processing units. Energy efficiency in WSNs is essential for ensuring a long network lifetime and dependable data transport in Internet of Things applications, where sensors are frequently placed in remote or unreachable locations. For IoT-enabled WSNs, this review article offers an extensive investigation of energy-optimized routing protocols. Their application in real-world circumstances, performance measures, and design principles are the main topics of the article. The review begins with a survey of conventional wireless sensor networks routing protocols and an evaluation of how well they balance end-to-end latency and energy usage. The paper then explores current developments in routing protocols for WSNs that are based on software-defined networking. It demonstrates how they could improve networks. to improve energy efficiency and network reliability by using dynamic resource allocation and centralized administration. In order to maximize energy consumption and prolong network lifetime in wireless sensor networks, the paper examines hybrid systems that include neural network architectures, metaheuristic algorithms, and reinforcement learning techniques. To meet the requirements of delay-sensitive Internet of Things applications, the assessment also addresses the difficulties with flexibility, mobility, and integration of clustered and routing systems. This study contributes significantly to our understanding of the state-of-the-art energy-optimized routing techniques for IoT-enabled WSNs by synthesizing the available literature and highlighting research needs. In order to fulfil the changing needs of Internet of Things applications across a range of sectors, the article proposes future research areas targeted at enhancing routing protocols and overcoming current obstacles