Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open channels
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Author
Buyya, RB; BELOGLAZOV, A; Abawajy, JDate
2010Source Title
Proceedings of the 16th International Conference on Parallel and Distributed Processing Techniques and Applications 2010Publisher
World Academy of Science, Engineering and TechnologyAffiliation
Computer Science and Software EngineeringMetadata
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Buyya, R. B., BELOGLAZOV, A. & Abawajy, J. (2010). Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open channels. Proceedings of the 16th International Conference on Parallel and Distributed Processing Techniques and Applications 2010, pp.1-12. World Academy of Science, Engineering and Technology.Access Status
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International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)
Abstract
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.
Keywords
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