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Profiling-based energy-aware recommendation system for cloud platforms
Citation
Amin, MB and Hussain, S and Han, M and Kang, BH and Ik, YY and Jun, S and Lee, S, Profiling-based energy-aware recommendation system for cloud platforms, Lecture Notes in Electrical Engineering 330: Proceedings of the International Conference on Computer Science and its Applications (CSA 2014) - Ubiquitous Information Technologies, 17-19 2014, Guam, pp. 851-859. ISBN 978-3-662-45401-5 (2015) [Refereed Conference Paper]
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Copyright Statement
Copyright 2015 Springer-Verlag Berlin Heidelberg
Official URL: http://doi.org.10.1007/978-3-662-45402-2 _121
DOI: doi:10.1007/978-3-662-45402-2_121
Abstract
With rise in energy costs, operational costs for managing cloud infrastructures are also increasing. This is an opportunity to present an energy-aware recommendation system for cloud platforms. This paper presents one such system that implements a pure software approach for generating energy efficient recommendations for cloud infrastructures. This system performs offline profiling of cloud nodes to generate energy-aware profiles which are later matched with runtime usage feed. According to the real-time data, energy efficient profile is matched and provided to provisioning for implementation; consequently, achieving an energy efficient cloud platform.
Item Details
Item Type: | Refereed Conference Paper |
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Keywords: | energy-efficiency, energy-aware, cloud computing, ganglia, profiling |
Research Division: | Information and Computing Sciences |
Research Group: | Data management and data science |
Research Field: | Data engineering and data science |
Objective Division: | Information and Communication Services |
Objective Group: | Information services |
Objective Field: | Information services not elsewhere classified |
UTAS Author: | Amin, MB (Dr Muhammad Bilal Amin) |
UTAS Author: | Kang, BH (Professor Byeong Kang) |
ID Code: | 109295 |
Year Published: | 2015 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2016-06-07 |
Last Modified: | 2021-03-25 |
Downloads: | 0 |
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