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Job scheduling in a heterogenous grid environment

Technical Report ·
DOI:https://doi.org/10.2172/860301· OSTI ID:860301
Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.
Research Organization:
Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA (US)
Sponsoring Organization:
USDOE Director. Office of Science. Office of AdvancedScientific Computing Research
DOE Contract Number:
AC02-05CH11231
OSTI ID:
860301
Report Number(s):
LBNL--54906; BnR: KJ0102000
Country of Publication:
United States
Language:
English

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