Budget Constrained Execution of Multiple Bag-of-Tasks Applications on the Cloud

Long Thai, B. Varghese, Adam Barker

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

9 Citations (Scopus)
36 Downloads (Pure)


Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade-offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be executed. In this paper, we propose and implement a heuristic algorithm that schedules tasks of multiple applications onto different cloud virtual machines in order to maximise performance while satisfying a given budget constraint. Current approaches are limited in task scheduling since they place a limit on the number of cloud resources that can be employed by the applications. However, in the proposed algorithm there are no such limits, and in comparison with other approaches, the algorithm on average achieves an improved performance of 10%. The experimental results also highlight that the algorithm yields consistent performance even with low budget constraints which cannot be achieved by competing approaches.
Original languageEnglish
Title of host publication2015 IEEE 8th International Conference on Cloud Computing (CLOUD)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Print)978-1-4673-7286-2
Publication statusPublished - 01 Jun 2015
Externally publishedYes


  • budgeting
  • cloud computing
  • resource allocation
  • scheduling
  • virtual machines
  • BoT application execution
  • bag-of-task application execution
  • budget constrained execution
  • cloud resources
  • cloud virtual machines
  • heuristic algorithm
  • performance maximisation
  • task scheduling
  • Cloud computing
  • Grid computing
  • Heuristic algorithms
  • Mathematical model
  • Parallel processing
  • Schedules
  • Scheduling
  • Bag-of-Tasks
  • Budget constraint
  • Cloud Computing
  • Multiple Applications


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