Experience with adapting a WS-BPEL runtime for eScience workflows

  • Authors:

  • Thilina Gunarathne;Chathura Herath;Eran Chinthaka;Suresh Marru

  • Affiliations:

  • Indiana University, Bloomington, IN;Indiana University, Bloomington, IN;Indiana University, Bloomington, IN;Indiana University, Bloomington, IN

  • Venue:
  • Proceedings of the 5th Grid Computing Environments Workshop
  • Year:
  • 2009

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Abstract

Scientists believe in the concept of collective intelligence and are increasingly collaborating with their peers, sharing data and simulation techniques. These collaborations are made possible by building eScience infrastructures. eScience infrastructures build and assemble various scientific workflow and data management tools which provide rich end user functionality while abstracting the complexities of many underlying technologies. For instance, workflow systems provide a means to execute complex sequence of tasks with or without intensive user intervention and in ways that support flexible reordering and reconfiguration of the workflow. As the workflow technologies continue to emerge, the need for interoperability and standardization clamorous. The Web Services Business Process Execution Language (WS-BPEL) provides one such standard way of defining workflows. WS-BPEL specification encompasses broad range of workflow composition and description capabilities that can be applied to both abstract as well as concrete executable components. Scientific workflows with their agile characteristics present significant challenges in embracing WS-BPEL for eScience purposes. In this paper we discuss the experiences in adopting a WS-BPEL runtime within an eScience infrastructure with reference to an early implementation of a custom eScience motivated BPEL like workflow engine. Specifically the paper focuses on replacing the early adopter research system with a widely used open source WS-BPEL runtime, Apache ODE, while retaining the interoperable design to switch to any WS-BPEL compliant workflow runtime in future. The paper discusses the challenges encountered in extending a business motivated workflow engine for scientific workflow executions. Further, the paper presents performance benchmarks for the developed system.