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Decentralized Enactment of BPEL Processes

机译:BPEL流程的分散制定

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This article presents ${ssr BPELcube}$, a framework comprising a scalable architecture and a set of distributed algorithms, which support the decentralized enactment of BPEL processes. In many application domains, BPEL processes are long-running, involve the exchange of voluminous data with external Web services, and are concurrently accessed by large numbers of users. In such context, centralized BPEL process execution engines pose considerable limitations in terms of scalability and performance. To overcome such problems, a scalable hypercube peer-to-peer topology is employed by ${ssr BPELcube}$ in order to organize an arbitrary number of nodes, which can then collaborate in the decentralized execution and monitoring of BPEL processes. Contrary to traditional clustering approaches, each node does not fully take charge of executing the whole process; rather, it contributes to the overall process execution by running a subset of the process activities and maintaining a subset of the process variables. Hence, the hypercube-based infrastructure acts as a single execution engine, where workload is evenly distributed among the participating nodes in a fine-grained manner. An experimental evaluation of ${ ssr BPELcube}$ and a comparison with centralized and clustered BPEL engine architectures demonstrate that the decentralized approach yields improved process execution times and throughput.
机译:本文介绍了$ {ssr BPELcube} $,这是一个包含可伸缩体系结构和一组分布式算法的框架,这些框架支持BPEL流程的分散式实现。在许多应用程序域中,BPEL流程运行时间很长,涉及与外部Web服务交换大量数据,并且被大量用户同时访问。在这种情况下,集中式BPEL流程执行引擎在可伸缩性和性能方面构成了相当大的限制。为了克服这些问题,$ {ssr BPELcube} $采用了可伸缩的超立方体对等拓扑,以组织任意数量的节点,然后可以在分散执行和监视BPEL流程中进行协作。与传统的聚类方法相反,每个节点不完全负责执行整个过程。相反,它通过运行过程活动的子集并维护过程变量的子集来促进整个过程的执行。因此,基于超多维数据集的基础结构充当单个执行引擎,其中工作负载以细粒度方式平均分布在参与节点之间。对$ {ssr BPELcube} $的实验评估以及与集中式和集群式BPEL引擎体系结构的比较表明,分散式方法可改善流程执行时间和吞吐量。

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