NDLI: An Innovative Energy-Aware Cloud Task Scheduling Framework

Content Provider	IEEE Xplore Digital Library
Author	Alahmadi, A. Che, D. Khaleel, M. Zhu, M.M. Ghodous, P.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. Lyon 1, Villeurbanne, France (Ghodous, P.) \|\| Dept. of Comput. Sci., Southern Illinois Univ., Carbondale, IL, USA (Alahmadi, A.; Che, D.; Khaleel, M.; Zhu, M.M.)
Abstract	With the increased popularity of cloud computing, the number and scales of cloud data centers have kept growing at unprecedented speeds. In the meanwhile, the energy consumption by the data centers has kept commensurately increasing as well. Therefore, the focus of cloud resource management and scheduling has relatively shifted from mere performance to also energy efficiency. In this paper, we present a novel, Energy-Aware Task Scheduling framework that makes integrated exploitation of the two well-known energy saving techniques, DVFS and VM Reuse, on cloud task scheduling in a data center. We present our scheduling approach and framework via a specific algorithm, called EATS-FFD, that assumes FFD as its base scheduling policy. With minor modification, the presented framework can be made to work with a different base scheduling policy, resulting in a correspondingly different scheduling algorithm. Our approach achieves better energy-efficiency without sacrificing system QoS. The effectiveness of our approach is evaluated under various experimental scenarios using the Cloud Report tool running on the open source CloudSim platform.
Starting Page	493
Ending Page	500
File Size	299458
Page Count	8
File Format	PDF
ISSN	21596190
e-ISBN	9781467372879
DOI	10.1109/CLOUD.2015.72
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Energy consumption Time-frequency analysis Job shop scheduling Processor scheduling Cloud Computing Task Scheduling VM Reuse Resource management Servers DVFS
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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