Alzamil, I, Djemame, K orcid.org/0000-0001-5811-5263, Armstrong, D et al. (1 more author) (2015) Energy-Aware Profiling for Cloud Computing Environments. In: Bull, P, Guan, L and Thomas, N, (eds.) Electronic Notes in Theoretical Computer Science. Twenty-ninth and thirtieth Annual UK Performance Engineering Workshops (UKPEW), 19 Sep 2014, Newcastle, UK. Elsevier , pp. 91-108.
Abstract
Cloud Computing has changed the way in which people use the IT resources today. Now, instead of buying their own IT resources, they can use the services offered by Cloud Computing with reasonable costs based on a "pay-per-use" model. However, with the wide adoption of Cloud Computing, the costs for maintaining the Cloud infrastructure have become a vital issue for the providers, especially with the large input of energy costs to underpin these resources. Thus, this paper proposes a system architecture that can be used for profiling the resources usage in terms of the energy consumption. From the profiled data, the application developers can enhance their energy-aware decisions when creating or optimising the applications to be more energy efficient. This paper also presents an adapted existing Cloud architecture to enable energy-aware profiling based on the proposed system. The results of the conducted experiments show energy-awareness at physical host and virtual machine levels.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Cloud Computing; Energy Efficiency; Energy-Aware Profiling; Energy Efficiency Metrics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Jul 2016 16:02 |
Last Modified: | 28 Sep 2016 15:50 |
Published Version: | http://dx.doi.org/10.1016/j.entcs.2015.10.021 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.entcs.2015.10.021 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:85685 |