Please use this identifier to cite or link to this item: https://doi.org/10.1109/AINA.2012.12
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dc.titleScaleStar: Budget conscious scheduling precedence-constrained many-task workflow applications in cloud
dc.contributor.authorZeng, L.
dc.contributor.authorVeeravalli, B.
dc.contributor.authorLi, X.
dc.date.accessioned2014-06-19T03:26:48Z
dc.date.available2014-06-19T03:26:48Z
dc.date.issued2012
dc.identifier.citationZeng, L., Veeravalli, B., Li, X. (2012). ScaleStar: Budget conscious scheduling precedence-constrained many-task workflow applications in cloud. Proceedings - International Conference on Advanced Information Networking and Applications, AINA : 534-541. ScholarBank@NUS Repository. https://doi.org/10.1109/AINA.2012.12
dc.identifier.isbn9780769546513
dc.identifier.issn1550445X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71704
dc.description.abstractTraditionally, the "best effort, cost free" model of Supercomputers/Grids does not consider pricing. Clouds have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on "pay-as-you-go" model. Large scale many-task workflow (MTW) may be suited for execution on Clouds due to its scale-* requirement (scale up, scale out, and scale down). In the context of scheduling, MTW execution cost must be considered based on users' budget constraints. In this paper, we address the problem of scheduling MTW on Clouds and present a budget-conscious scheduling algorithm, referred to as Scale Star (or Scale-*). Scale Star assigns the selected task to a virtual machine with higher comparative advantage which effectively balances the execution time-and-monetary cost goals. In addition, according to the actual charging model, an adjustment policy, refer to as DeSlack, is proposed to remove part of slack without adversely affecting the overall make span and the total monetary cost. We evaluate Scale Star with an extensive set of simulations and compare with the most popular HEFT-based LOSS3 algorithm and demonstrate the superior performance of Scale Star. © 2012 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/AINA.2012.12
dc.sourceScopus
dc.subjectbudget
dc.subjectCloud computing
dc.subjectmakespan
dc.subjectscheduling
dc.subjectworkflow
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/AINA.2012.12
dc.description.sourcetitleProceedings - International Conference on Advanced Information Networking and Applications, AINA
dc.description.page534-541
dc.identifier.isiut000309071500074
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