Energy-Efficient Routing Protocol for Next-Generation Application in the Internet of Things

Abstract

In the evolving landscape of Wireless Sensor Networks (WSN) and the Internet of Things (IoT), efficient energy utilizations and optimized routing protocols are crucial for sustaining network longevity and performance. This study presents a analysis of existing energy efficient routing protocols and proposes an innovative solution leveraging fuzzy clustering, machine learning and hybrid optimization techniques. Through comparative evaluation of various methodologies including metaheuristic- enhanced frameworks, probabilistic algorithms, a neuro-fuzzy approaches, this research identifies performance metrics such as energy savings, network scalability and efficiency.

The findings demonstrate that the the call proposed significantly reduces energy consumption while enhancing throughput and minimizes latency, making it suitable for diverse IoT applications. Real- world feasibility is assessed highlighting strengths like robustness and adaptability, alongside acknowledging such as computational complexity and hardware dependencies. This study contributes valuable insights into the development of next- generation energy- aware routing protocols, paving the way for future innovations in IoT and WSN infrastructures.