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Green cloud computing: reduced overload with a better architecture

Authors

Dhusia Kalyani, Rizvi Z. Ahsan, Firoz Neda, Telgote Stuti , and Ramteke W. Pramod1

Abstract

Software systems architects had been continually facing challenges of scaling up software systems architectures. Scaling up the architectures to meet these needs certainly introduces additional energy cost. Improvement of applications, algorithms, energy efficient hardware has been done to achieve energy efficiency. Reducing the energy demands in such architectures is always challenging. The greatest environmental challenge today is e-wastes and energy crisis, bringing green computing in the limelight. Green computing requires algorithms and mechanisms to be redesigned for energy efficiency. In accordance to the state of art for distributed software architectures, are not aware on green cloud computing while the implementation needs, changing the whole infrastructure cost effectively.

Software architectures don’t provide the primitives for reasoning and managing power consumption. In present work, an energy efficient resource management system for virtualized Cloud data centers that reduces operational costs and provides required Quality of Service (QoS) has been proposed and fulfilled. Our proposal towards software engineering demands to be green aware, where the software engineering and design activities should not only be judged by their technical merits, but also by their contributions to energy savings. In particular, the software system architecture seems to be adequate to address green-aware concerns but need revival. Software architectures should be green-aware, providing power management mechanisms as part of the architecture. The results of present work improvised that the proposed technique brings substantial energy savings, while ensuring reliable QoS. This justifies further investigation and development of the proposed resource management system.

Article Details

Published

2015-08-28

Section

Articles

How to Cite

Green cloud computing: reduced overload with a better architecture. (2015). International Journal of Engineering and Computer Science, 4(08). https://ijecs.in/index.php/ijecs/article/view/3362