Energy Saving Techniques Comparison for Green Computing in Cloud Server

Bilal Ahmad, Sally I McClean, D.K. Charles, G Parr

Research output: Contribution to journalConference article

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Abstract

- The IT industry has been revolutionized in the past few
decades. Cloud Computing companies (Google, Yahoo, Gaikai,
ONLIVE, Amazon and eBay) use large data centers which are
comprised of virtual computers that are placed globally and
require a lot of power cost to maintain. Demand for energy
consumption is increasing day by day in IT firms. Therefore,
Cloud Computing companies face challenges towards the
maintenance of power costs. Energy consumption is dependent
upon several factors, e.g., service level agreement, virtual
machine selection techniques, optimization policies, workload
types etc. We address a solution for the energy saving problem
by enabling dynamic voltage and frequency scaling technique for
gaming data centers. The dynamic voltage and frequency scaling
technique is compared against non-power aware and static
threshold detection techniques. This helps service providers to
meet the quality of service and quality of experience constraints
by meeting service level agreements. The CloudSim platform is
used for implementation of the scenario in which game traces are
used as a workload for testing the technique. Selection of better
techniques can help gaming servers to save energy cost and
maintain a better quality of service for users placed globally. The
novelty of the work provides an opportunity to investigate which
technique behaves better, i.e., dynamic, static or non-power
aware. The results demonstrate that less energy is consumed by
implementing a dynamic voltage and frequency approach in
comparison with static threshold consolidation or non-power
aware technique.
Original languageEnglish
Pages (from-to)192
Number of pages201
JournalInternational Journal On Advances in Intelligent Systems
Publication statusPublished - 1 Dec 2018

Keywords

  • dynamic streaming
  • Energy Saving Technique
  • Dynamic Frequency Scaling

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