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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
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
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