A review energy-efficient task scheduling algorithms in cloud computing

Saleh Atiewi, Salman Yussof, Mohd Ezanee, Muder Almiani

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

9 Citations (Scopus)

Abstract

Cloud computing is a model for delivering information technology services, wherein resources are retrieved from the Internet through web-based tools and applications instead of a direct connection to a server. The capability to provision and release cloud computing resources with minimal management effort or service provider interaction led to the rapid increase of the use of cloud computing. Therefore, balancing cloud computing resources to provide better performance and services to end users is important. Load balancing in cloud computing means balancing three important stages through which a request is processed. The three stages are data center selection, virtual machine scheduling, and task scheduling at a selected data center. User task scheduling plays a significant role in improving the performance of cloud services. This paper presents a review of various energy-efficient task scheduling methods in a cloud environment. A brief analysis of various scheduling parameters considered in these methods is also presented. The results show that the best power-saving percentage level can be achieved by using both DVFS and DNS.

Original languageEnglish
Title of host publication2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467384902
DOIs
Publication statusPublished - 16 Jun 2016
EventIEEE Long Island Systems, Applications and Technology Conference, LISAT 2016 - Farmingdale, United States
Duration: 29 Apr 2016 → …

Publication series

Name2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016

Other

OtherIEEE Long Island Systems, Applications and Technology Conference, LISAT 2016
CountryUnited States
CityFarmingdale
Period29/04/16 → …

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Atiewi, S., Yussof, S., Ezanee, M., & Almiani, M. (2016). A review energy-efficient task scheduling algorithms in cloud computing. In 2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016 [7494108] (2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LISAT.2016.7494108