A deadline and cost constrained optimization algorithm for scheduling applications in Grids based on proportional share systems

Dazhen Wang*, Kwang Mong Sim, Benyun SHI

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

Since computation of Grids enable the sharing, selection, query and aggregation of geographically distributed resources for solving large-scale problems, developing mechanisms for Grid resource scheduling is a complex undertaking problem. We had investigated several famous schedule methods proposed by Nimrod-G, a famous computational economy framework for regulating the supply and demand for resources. In this paper, we propose a novel scheduling algorithm, called deadline and cost constrained optimization algorithm, which extends Buyya's cost optimization and time optimization algorithm, keeping the cost and time optimization at same time. Our optimization algorithm, which is based on proportional share (PS), allows users to bid higher in order to gain more resource shares. Therefore, this algorithm adjusts a user bid periodically on these systems in order to finish the application on time. Empirical results show that the algorithm had better performance than with conventional algorithms.

Original languageEnglish
Title of host publicationProceedings of the International Symposium on Electronic Commerce and Security, ISECS 2008
Pages46-50
Number of pages5
DOIs
Publication statusPublished - 2008
EventInternational Symposium on Electronic Commerce and Security, ISECS 2008 - Guangzhou, China
Duration: 3 Aug 20085 Aug 2008

Publication series

NameProceedings of the International Symposium on Electronic Commerce and Security, ISECS 2008

Conference

ConferenceInternational Symposium on Electronic Commerce and Security, ISECS 2008
Country/TerritoryChina
CityGuangzhou
Period3/08/085/08/08

Scopus Subject Areas

  • Marketing
  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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