An Innovative Energy-Aware Cloud Task Scheduling Framework

Abdulrahman Alahmadi, Dunren Che, Mustafa Khaleel, Michelle M. Zhu, Parsia Ghodous

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015
EditorsCalton Pu, Ajay Mohindra
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages493-500
Number of pages8
ISBN (Electronic)9781467372879
DOIs
StatePublished - 19 Aug 2015
Event8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States
Duration: 27 Jun 20152 Jul 2015

Other

Other8th IEEE International Conference on Cloud Computing, CLOUD 2015
CountryUnited States
CityNew York
Period27/06/152/07/15

Keywords

  • Cloud Computing
  • DVFS
  • Energy consumption
  • Task Scheduling
  • VM Reuse

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  • Cite this

    Alahmadi, A., Che, D., Khaleel, M., Zhu, M. M., & Ghodous, P. (2015). An Innovative Energy-Aware Cloud Task Scheduling Framework. In C. Pu, & A. Mohindra (Eds.), Proceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015 (pp. 493-500). [7214082] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLOUD.2015.72