Energy-Efficient Scheduling Algorithms for Multi-Tenant CloudBased Data Centers
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V5I1P101Keywords:
Energy efficiency, Scheduling algorithms, Cloud computing, Multi-tenant data centers, Virtual machine allocation, Workload consolidation, Green computingAbstract
The rapid expansion of cloud computing has led to significant energy consumption in data centers, raising concerns regarding environmental sustainability and operational costs. Energy-efficient scheduling algorithms are pivotal in addressing these challenges by optimizing resource allocation and minimizing energy usage. This paper reviews various scheduling strategies tailored for multi-tenant cloud-based data centers, focusing on task scheduling, Virtual Machine (VM) allocation, and workload consolidation. Techniques such as Dynamic Voltage and Frequency Scaling (DVFS), task migration, and deadline-aware scheduling are examined for their effectiveness in enhancing energy efficiency. The study highlights the principles behind these algorithms, their implementation challenges, and the potential for innovation in energy-aware scheduling methods. Case studies illustrate the practical application of these algorithms, demonstrating substantial reductions in energy consumption without compromising performance. As cloud service demands continue to rise, integrating advanced scheduling techniques is essential for achieving sustainable cloud computing environments
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References
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