Kavanagh, R orcid.org/0000-0002-9357-2459, Armstrong, D, Djemame, K orcid.org/0000-0001-5811-5263 et al. (2 more authors) (2016) Towards an Energy-Aware Cloud Architecture for Smart Grids. In: Altmann, J, Silaghi, GC and Rana, OF, (eds.) Economics of Grids, Clouds, Systems, and Services. 12th International Conference, GECON 2015, 15-17 Sep 2015, Cluj-Napoca, Romania. Lecture Notes in Computer Science (9512). Springer International Publishing , Cham, Switzerland , pp. 190-204. ISBN 978-3-319-43176-5
Abstract
Energy consumption in Cloud computing is a significant issue in regards to aspects such as the cost of energy, cooling in the data center and the environmental impact of cloud data centers. Smart grids offers the prospect of dynamic costs for a data center’s energy usage. These dynamic costs can be passed on to Cloud users providing incentives for users to moderate their load while also ensuring the Cloud providers are insulated from fluctuations in the cost of energy. The first step towards this is an architecture that focuses on energy monitoring and usage prediction. We provide such an architecture at both the PaaS and IaaS layers, resulting in energy metrics for applications, VMs and physical hosts, which is key to enabling active demand in cloud data centers. This architecture is demonstrated through our initial results utilising a generic use case, providing energy consumption information at the PaaS and IaaS layers. Such monitoring and prediction provides the groundwork for providers passing on energy consumption costs to end users. It is envisaged that the resulting varying price associated with energy consumption can help motivate the formation of methods and tools to support software developers aiming to optimise energy efficiency and minimise the carbon footprint of Cloud applications.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer International Publishing. This is an author produced version of a paper published in Lecture Notes in Computer Science. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-43177-2_13. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Cloud Computing; Energy; Energy Efficiency; IaaS; Monitoring; PaaS; Power |
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) |
Funding Information: | Funder Grant number EU - European Union 610874 |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Oct 2016 15:37 |
Last Modified: | 16 Jan 2018 17:14 |
Published Version: | https://doi.org/10.1007/978-3-319-43177-2_13 |
Status: | Published |
Publisher: | Springer International Publishing |
Series Name: | Lecture Notes in Computer Science |
Identification Number: | 10.1007/978-3-319-43177-2_13 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99115 |