Online job provisioning for large scale science experiments over an optical grid infrastructure

Xiang Yu, Chunming Qiao, Dantong Yu

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

4 Scopus citations


Many emerging science experiments require that the massive data generated by big instruments be accessible and analyzed by a large number of geographically dispersed users. Such large scale science experiments are enabled by an Optical Grid infrastructure which integrates Grid software with a WDM network. This paper studies the following problem in an Optical Grid environment: given an online job request, how to optimally find a host to execute the job, taking into account the need to stage missing input files stored at other places, with the goal of satisfying the job's QoS requirements, subject to dynamic computing and network resource usage status? We first formulate the optimization problem as a Mixed Integer Linear Programming (MILP). As the MILP solution quickly gets intractable when the network size grows larger, we also propose an adaptive heuristic called AOJP. Our simulation results demonstrate both the effectiveness and the efficiency of AOJP.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM Workshops 2009
StatePublished - 2009
Externally publishedYes
EventIEEE INFOCOM Workshops 2009 - Rio de Janeiro, Brazil
Duration: Apr 19 2009Apr 25 2009

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


OtherIEEE INFOCOM Workshops 2009
CityRio de Janeiro

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


  • Grid
  • Job provisioning
  • Large scale science experiment
  • Resource co-scheduling
  • WDM network


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