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Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers
Citation
Garg, SK and Yeo, CS and Anandasivam, A and Buyya, R, Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers, Journal of Parallel and Distributed Computing, 71, (6) pp. 732-749. ISSN 0743-7315 (2011) [Refereed Article]
Copyright Statement
Copyright 2010 Elsevier
DOI: doi:10.1016/j.jpdc.2010.04.004
Abstract
The use of High Performance Computing (HPC) in commercial and consumer IT applications is becoming popular. HPC users need the ability to gain rapid and scalable access to high-end computing capabilities. Cloud computing promises to deliver such a computing infrastructure using data centers so that HPC users can access applications and data from a Cloud anywhere in the world on demand and pay based on what they use. However, the growing demand drastically increases the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high energy cost which will reduce the profit margin of Cloud providers, but also high carbon emissions which are not environmentally sustainable. Hence, there is an urgent need for energy-efficient solutions that can address the high increase in the energy consumption from the perspective of not only the Cloud provider, but also from the environment. To address this issue, we propose near-optimal scheduling policies that exploit heterogeneity across multiple data centers for a Cloud provider. We consider a number of energy efficiency factors (such as energy cost, carbon emission rate, workload, and CPU power efficiency) which change across different data centers depending on their location, architectural design, and management system. Our carbon/energy based scheduling policies are able to achieve on average up to 25% of energy savings in comparison to profit based scheduling policies leading to higher profit and less carbon emissions.
Item Details
Item Type: | Refereed Article |
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Keywords: | cloud computing, high performance computing (HPC), energy-efficient scheduling, dynamic voltage scaling (DVS), green IT |
Research Division: | Information and Computing Sciences |
Research Group: | Distributed computing and systems software |
Research Field: | Distributed systems and algorithms |
Objective Division: | Environmental Policy, Climate Change and Natural Hazards |
Objective Group: | Mitigation of climate change |
Objective Field: | Management of greenhouse gas emissions from information and communication services |
UTAS Author: | Garg, SK (Dr Saurabh Garg) |
ID Code: | 93854 |
Year Published: | 2011 |
Web of Science® Times Cited: | 185 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2014-08-19 |
Last Modified: | 2014-12-08 |
Downloads: | 0 |
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