Monitoring data dependencies in concurrent process execution through delta-enabled grid services

  • Authors:

  • Susan D. Urban;Yang Xiao;Luther Blake;Suzanne W. Dietrich

  • Affiliations:

  • Department of Computer Science, Texas Tech University, Box 43104, Lubbock, TX 79409 3104, USA.;Department of Computer Science and Engineering, School of Computing and Informatics, Arizona State University, P.O. Box 878809, Tempe, AZ 85287 8809, USA.;Department of Computer Science and Engineering, School of Computing and Informatics, Arizona State University, P.O. Box 878809, Tempe, AZ 85287 8809, USA.;Division of Mathematical and Natural Sciences, Arizona State University, P.O. Box 37100, Phoenix, AZ 85069 7100, USA

  • Venue:
  • International Journal of Web and Grid Services
  • Year:
  • 2009

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Abstract

This paper presents our results with monitoring data dependencies among concurrently executing, distributed processes that execute over grid services. The research has been conducted in the context of the DeltaGrid project, focusing on the development of a semantically robust execution environment for the composition of grid services. Delta-Enabled Grid Services (DEGS) are a foundational aspect of the DeltaGrid environment, extending grid services with the capability of recording incremental data changes, known as deltas. Deltas generated by DEGS are forwarded to a Process History Capture System (PHCS) that organises deltas from distributed sources into a global, time-sequenced schedule of data changes. The design and construction of DEGS is presented, along with the storage and indexing techniques for merging deltas from multiple DEGS to create a global schedule of data changes that can be analysed to determine how the failure and recovery of one process can potentially affect other data-dependent processes. The paper also summarises the performance results for the global history construction and retrieval process.