Scheduling workflow in cloud computing based on ant colony optimization algorithm

  • Yue Zhou
  • , Xinli Huang*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Scopus citations

Abstract

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. So how to schedule applications to cloud resources and the execution time should be taken into account. In this paper, we propose a scheduling strategy based on ant colony optimization (ACO) and two-way ants mechanism is introduced. Setting the pheromone threshold is to avoid the premature phenomenon, in addition, taking a two-tier search strategy and introducing pre-execution time is to avoid the local optimum so that tasks can be assigned to highest efficient computing resources. The simulation results show that the algorithm can greatly shorten the time to find the computing resource in cloud computing environment and significantly improve the efficiency.

Original languageEnglish
Title of host publicationProceedings - 2013 6th International Conference on Business Intelligence and Financial Engineering, BIFE 2013
EditorsLean Yu, Rongda Chen, Shouyang Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages57-61
Number of pages5
ISBN (Electronic)9781479947775
DOIs
StatePublished - 18 Nov 2014
Event6th International Conference on Business Intelligence and Financial Engineering, BIFE 2013 - Hangzhou, Zhejiang, China
Duration: 14 Nov 201316 Nov 2013

Publication series

NameProceedings - 2013 6th International Conference on Business Intelligence and Financial Engineering, BIFE 2013

Conference

Conference6th International Conference on Business Intelligence and Financial Engineering, BIFE 2013
Country/TerritoryChina
CityHangzhou, Zhejiang
Period14/11/1316/11/13

Keywords

  • ACO
  • cloud computing
  • pre-execution
  • two-tier search
  • two-way ants
  • workflow

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