Carbon-Aware Intelligent Scheduling Framework for Energy-Efficient Green Cloud Computing

Om Priya V; Dr.D.Uma Nandhini

doi:10.36948/ijfmr.2026.v08i03.79043

Carbon-Aware Intelligent Scheduling Framework for Energy-Efficient Green Cloud Computing

Author(s)	Ms. Om Priya V, Dr.D.Uma Nandhini
Country	India
Abstract	Cloud computing is widely used in modern industries for storing data, running applications, and managing online services. The rapid growth of cloud computing has significantly increased the energy consumption of large data centers, which also leads to higher carbon emissions and environmental pollution. Most traditional cloud scheduling methods mainly focus on improving system performance and resource utilization without considering energy efficiency and environmental impact. As a result, green cloud computing has become an important research area for developing sustainable and energy-efficient cloud infrastructures. This paper examines various existing studies related to energy-efficient and carbon-aware cloud computing systems. The paper analyzes various approaches to reducing energy consumption and carbon emissions in cloud data centers, including workload prediction, intelligent scheduling, virtualization, carbon-aware resource allocation, and hybrid optimization techniques. Several machine learning and artificial intelligence methods, such as Long Short-Term Memory (LSTM), Particle Swarm Optimization (PSO), Genetic Algorithms (GA), and Grey Wolf Optimization (GWO) used in existing research are also discussed. The review mainly focuses on cloud workload management, carbon intensity analysis, and intelligent scheduling strategies used in green cloud computing environments. The analysis of existing studies shows that intelligent scheduling and carbon-aware resource management can significantly reduce energy consumption and environmental impact while maintaining cloud performance and service quality. This review highlights the advantages, limitations, and challenges of current approaches and emphasizes the importance of developing sustainable cloud computing systems for future digital infrastructure.
Keywords	Green Cloud Computing, Energy-efficient Scheduling, Carbon-aware Resource Allocation, Cloud Workload Management, Intelligent Optimization Techniques
Field	Computer > Network / Security
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-22
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.79043

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Carbon-Aware Intelligent Scheduling Framework for Energy-Efficient Green Cloud Computing

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