3rd International ICST Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications

Research Article

Optimizing Distributed Execution of WS-BPEL Processes in Heterogeneous Computing Environments

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  • @INPROCEEDINGS{10.1007/978-3-642-10625-5_49,
        author={Qishi Wu and Yi Gu and Liang Bao and Wei Jia and Huichen Dai and Ping Chen},
        title={Optimizing Distributed Execution of WS-BPEL Processes in Heterogeneous Computing Environments},
        proceedings={3rd International ICST Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications},
        proceedings_a={AAA-IDEA},
        year={2012},
        month={10},
        keywords={WS-BPEL workflow mapping optimization heuristic algorithm},
        doi={10.1007/978-3-642-10625-5_49}
    }
    
  • Qishi Wu
    Yi Gu
    Liang Bao
    Wei Jia
    Huichen Dai
    Ping Chen
    Year: 2012
    Optimizing Distributed Execution of WS-BPEL Processes in Heterogeneous Computing Environments
    AAA-IDEA
    Springer
    DOI: 10.1007/978-3-642-10625-5_49
Qishi Wu1,*, Yi Gu1,*, Liang Bao2,*, Wei Jia2,*, Huichen Dai2,*, Ping Chen2,*
  • 1: University of Memphis
  • 2: XiDian University
*Contact email: qishiwu@memphis.edu, yigu@memphis.edu, baoliang@mail.xidian.edu.cn, weijia@mail.xidian.edu.cn, huichendai@mail.xidian.edu.cn, pingchen@mail.xidian.edu.cn

Abstract

Workflow-structured Web service composition is an emerging computing paradigm for constructing next-generation large-scale distributed applications within and across organizational boundaries. Mapping such application workflows in heterogeneous environments and optimizing their performance in terms of quick response and high scalability are vital to the success of these distributed applications. Workflows with complex execution semantics and dependencies are typically modeled as directed acyclic graphs. We construct cost models to estimate data processing and transfer overheads and formulate the restricted workflow mapping for minimum total execution time as an NP-complete optimization problem. We propose a heuristic approach to this problem that recursively computes and maps the critical path to network nodes using a dynamic programming-based procedure. The performance superiority of the proposed approach is illustrated by an extensive set of simulations and further verified by experimental results from a real network in comparison with existing methods.