Energy-Efficient Communication Protocols for Green Wireless Networks: Algorithms, Strategies, and Real-World Implementations

Abstract

With the surging demand for wireless communication, the need for energy-efficient and sustainable network solutions has emerged to be increasingly critical. The paper primarily delves into the development and optimisation of energy-efficient communication protocols designed to reduce the power consumed in wireless networks while still maintaining reliability and high performance. Through a comprehensive analysis of diverse network components, including mobile device base stations, and data transmission processes, the study concentrates on the development of algorithms that minimise the energy consumed to a significant extent. Fundamental strategies taken into consideration range from coding and adaptive modulation, sleep mode techniques and energy-aware routing. The use of machine learning (ML) algorithms, especially in reinforcing learning and predictive analytics, paves the way for dynamic adjustment of network parameters in terms of real-time traffic conditions and user behaviour. Integrating renewable energy inclusive of an array of sources like solar and wind into wireless network infrastructures is also explored and examined, paving a way for both resilience and sustainability against power grid failures. Experimental evaluation and the simulation reveal that the proposed energy-efficient protocols may significantly minimise the power consumed but still not compromise with the quality of service (QoS) provided. The findings demonstrates the pivotal role of energy efficiency in the evolution of next-generation wireless networks alongside the provision actionable insights for network operators, designers, and policymakers.