Green Computing and Optimization in Wireless Sensor Networks: A Holistic Approach for Sustainable Networks

Abstract

Wireless Sensor Networks (WSNs) are a key technology for modern networks due to their high efficiency and widespread applications in various domains, including environmental monitoring, smart homes, and industrial systems. However, WSNs face challenges regarding excessive power consumption and limited resources, which can negatively impact both performance and sustainability. Green computing emerges as a promising paradigm to address these issues, focusing on the optimization of energy consumption and resource utilization, while maintaining the quality of service. This paper explores recent developments in green computing for WSNs, considering various aspects such as energy-efficient network design, low-power hardware components, and energy management techniques. The study highlights the significance of employing optimization algorithms to achieve energy conservation, including centralized and distributed approaches, as well as hybrid schemes that integrate machine learning.