A cost-effective scheduling algorithm for scientific workflows in clouds

Mengxia Zhu, Qishi Wu, Yang Zhao

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

30 Scopus citations

Abstract

Cloud computing enables the delivery of computing, software, storage, and data access through web browsers as a metered service. In addition to commercial applications, an increasing number of large-scale workflow-based scientific applications are being supported by cloud computing. In order to meet the rapidly growing and dynamic computing demands of scientific users, the cloud service provider needs to employ efficient and cost-effective job schedulers to guarantee workflow completion time as well as improve resource utilization for high throughput. Based on rigorous cost models, we formulate a delay-constrained optimization problem to maximize resource utilization and propose a two-step workflow scheduling algorithm to minimize the cloud overhead within a user-specified execution time bound. The extensive simulation results illustrate that our approach consistently achieves lower computing overhead or higher resource utilization than existing methods within the execution time bound. Our approach also significantly reduces the total execution time by strategically selecting appropriate mapping nodes for prioritized modules.

Original languageEnglish
Title of host publication2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012
Pages256-265
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012 - Austin, TX, United States
Duration: 1 Dec 20123 Dec 2012

Publication series

Name2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012

Other

Other2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012
CountryUnited States
CityAustin, TX
Period1/12/123/12/12

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Keywords

  • Scientific workflow
  • cloud computing
  • workflow scheduling

Cite this

Zhu, M., Wu, Q., & Zhao, Y. (2012). A cost-effective scheduling algorithm for scientific workflows in clouds. In 2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012 (pp. 256-265). [6407766] (2012 IEEE 31st International Performance Computing and Communications Conference, IPCCC 2012). https://doi.org/10.1109/PCCC.2012.6407766