Review of Cloud Datacenter Operations Optimization of Renewable – Energy - Aware Resource Scheduling Algorithms

Abstract

Cloud data centers face increasing energy requirements, and renewable energy scheduling algorithm provides a promising solution to improve energy efficiency and stability. This review paper examines various planning techniques to integrate into renewable energy sources, such as sun and wind, and cloud computing operations. Important methods that have been detected include dynamic voltage and frequency scaling (DVF), task consolidation, and energy intersections such as renewable planning including strategies that interact workloads with renewable energy availability. In addition, future indicative and adaptive approaches that use forecasts and real-time data for skilled resource allocation are discussed. While these algorithms provide significant potential, challenges remain, including renewable energy, integration complications, and unpredictable scalability problems. Emerging trends, such as energy storage, machine learning, and progress in smart online technologies, provide opportunities to increase the performance of planning algorithms. Also identifies intervals, especially in algorithm efficiency, forecast for renewable energy, and economic viability.