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S, Gowri, Rathi, Jaganathan. (1404). Smart Scheduling for Green Cloud Data Centers: Reducing Energy Consumption through Innovative Algorithms. فناوری آموزش, (), -. doi: 10.22061/jecei.2025.12132.855
Gowri S; Jaganathan Rathi. "Smart Scheduling for Green Cloud Data Centers: Reducing Energy Consumption through Innovative Algorithms". فناوری آموزش, , , 1404, -. doi: 10.22061/jecei.2025.12132.855
S, Gowri, Rathi, Jaganathan. (1404). 'Smart Scheduling for Green Cloud Data Centers: Reducing Energy Consumption through Innovative Algorithms', فناوری آموزش, (), pp. -. doi: 10.22061/jecei.2025.12132.855
S, Gowri, Rathi, Jaganathan. Smart Scheduling for Green Cloud Data Centers: Reducing Energy Consumption through Innovative Algorithms. فناوری آموزش, 1404; (): -. doi: 10.22061/jecei.2025.12132.855

Smart Scheduling for Green Cloud Data Centers: Reducing Energy Consumption through Innovative Algorithms

Journal of Electrical and Computer Engineering Innovations (JECEI)
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 20 مهر 1404
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2025.12132.855
نویسندگان
Gowri S* 1؛ Jaganathan Rathi2
1Department of Computer Science ,K. S. Rangasamy College of Arts and Science (Autonomous), Tiruchengode, Tamil Nadu, India
2Department of Computer Science, , K. S. Rangasamy College of Arts and Science(Autonomous), Tiruchengode, Tamil Nadu, India.
تاریخ دریافت: 28 خرداد 1404،  تاریخ بازنگری: 07 مهر 1404،  تاریخ پذیرش: 15 مهر 1404 
چکیده
Background and Objectives: Cloud computing can play a vital role in promoting environmental sustainability by leveraging eco-friendly dedicated servers that adhere to green computing standards. The concept of "green cloud computing" revolves around harnessing cutting-edge technologies to minimize the environmental footprint of computing systems. One of the significant challenges in cloud-based systems is task scheduling, which must be optimized to enhance system efficiency, user experience, and environmental sustainability.
Method: This paper proposes a novel Hybrid HEES (Hierarchical Energy-Efficient Scheduling) method that optimizes energy consumption and task scheduling in cloud computing environments. By combining genetic algorithm optimization, workflow-based scheduling, and energy-aware resource allocation, HEES achieves significant reductions in energy consumption and average task completion time.
Results: The method is evaluated through simulations, demonstrating its effectiveness in optimizing energy efficiency and task scheduling performance. The Hybrid HEES method has the potential to reduce energy consumption, improve computing performance, and enhance sustainability in cloud computing environments.
Conclusion: To evaluate a proposed HEES method through cloudsim 3.0 simulations, the numerical results confirm the effectiveness of HEES algorithm, which achieves average Energy consumption performance improvements of around 12% compared to GP and 8% compared to RR existing methods.
کلیدواژه‌ها
Cloud computing؛ Virtual Machine؛ Energy؛ cost؛ HEES
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