Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges
Buyya, Rajkumar, Beloglazov, Anton and Abawajy, Jemal 2010, Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges, in PDPTA 2010 : Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications, CSREA Press, United States of America, pp. 6-17.
Parallel and Distributed Processing Techniques and Applications Conference
Place of publication
United States of America
Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.
Field of Research
080504 Ubiquitous Computing
Socio Economic Objective
890299 Computer Software and Services not elsewhere classified
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