Scheduling Workloads of Workflows with Unknown Task Runtimes

Workflows are important computational tools in many branches of science, and because of the dependencies among their tasks and their widely different characteristics, scheduling them is a difficult problem. Most research on scheduling workflows has focused on the offline problem of minimizing the ma...

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Bibliographic Details
Published in2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing pp. 606 - 616
Main Authors Ilyushkin, Alexey, Ghit, Bogdan, Epema, Dick
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2015
Subjects
Approximation methods
backfilling
e-Science
online
Periodic structures
Processor scheduling
Program processors
reservation
Runtime
Schedules
Scheduling
workflows
workloads
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Summary:Workflows are important computational tools in many branches of science, and because of the dependencies among their tasks and their widely different characteristics, scheduling them is a difficult problem. Most research on scheduling workflows has focused on the offline problem of minimizing the make span of single workflows with known task runtimes. The problem of scheduling multiple workflows has been addressed either in an offline fashion, or still with the assumption of known task runtimes. In this paper, we study the problem of scheduling workloads consisting of an arrival stream of workflows without task runtime estimates. The resource requirements of a workflow can significantly fluctuate during its execution. Thus, we present four scheduling policies for workloads of workflows with as their main feature the extent to which they reserve processors to workflows to deal with these fluctuations. We perform simulations with realistic synthetic workloads and we show that any form of processor reservation only decreases the overall system performance and that a greedy backfilling-like policy performs best.
DOI:10.1109/CCGrid.2015.27