An Overview of Green Computing for Smart Energy Management

Abstract

Surging power demands across modern data centers and high-performance computing (HPC) architectures present major economic and ecological challenges, highlighting the urgent need for intelligent, sustainable energy management solutions. Green computing addresses these issues by deploying interconnected computational resources operating on standardized communication protocols to balance energy supply with dynamic workload demands. By utilizing heuristic scheduling, live migration strategies, and resource allocation algorithms, green computing minimizes power consumption, optimizes server performance, and reduces reliance on hazardous materials. This special issue overview examines recent interdisciplinary advancements that integrate Knowledge Engineering, mathematical modeling, big data analytics, and artificial intelligence into green computing frameworks. The compiled research covers a broad range of applications, including heuristic secure routing protocols for network energy efficiency, data mining for atmospheric pollution monitoring, digital twin simulations in the new energy vehicle sector, Bayesian risk modeling in energy finance, and AI-driven supply chain optimization. Empirical findings across these studies demonstrate significant quantitative benefits, such as reduced latency, improved prediction accuracy, extended network longevity, and enhanced resource utilization rates. Ultimately, this collection proves that combining green computing principles with advanced digital technologies provides a robust foundation for effective environmental governance, grid resilience, and sustainable economic growth.