CMS workflow execution using intelligent job scheduling and data access strategies.
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IEEE TNS CMS Workflow Scheduling ...
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Authors
Hasham, KhawarDelgado Peris, Antonio
Anjum, Ashiq

Evans, Dave
Gowdy, Stephen
Hernandez, José M.
Huedo, Eduardo
Hufnagel, Dirk
van Lingen, Frank
McClatchey, Richard
Metson, Simon
Affiliation
University of the West of EnglandEuropean Center for Nuclear Research
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
Fermi National Accelerator Laboratory
Universidad Complutense de Madrid
University of Bristol
Issue Date
2011-06
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Show full item recordAbstract
Complex scientific workflows can process large amounts of data using thousands of tasks. The turnaround times of these workflows are often affected by various latencies such as the resource discovery, scheduling and data access latencies for the individual workflow processes or actors. Minimizing these latencies will improve the overall execution time of a workflow and thus lead to a more efficient and robust processing environment. In this paper, we propose a pilot job concept that has intelligent data reuse and job execution strategies to minimize the scheduling, queuing, execution and data access latencies. The results have shown that significant improvements in the overall turnaround time of a workflow can be achieved with this approach. The proposed approach has been evaluated, first using the CMS Tier0 data processing workflow, and then simulating the workflows to evaluate its effectiveness in a controlled environment.Citation
Hasham, K. et al. (2011) 'CMS workflow execution using intelligent job scheduling and data access strategies', IEEE Transactions on Nuclear Science. 58(3), pp.1221 - 1232. DOI:10.1109/TNS.2011.2146276Publisher
IEEEJournal
IEEE Transactions on Nuclear ScienceDOI
10.1109/TNS.2011.2146276Type
ArticleLanguage
enISSN
0018-9499EISSN
1558-1578ae974a485f413a2113503eed53cd6c53
10.1109/TNS.2011.2146276