Decentralized enactment of bpel processes
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The document presents BPEL Cube, a decentralized framework for executing BPEL processes using a hypercube peer-to-peer architecture to improve scalability and performance. It highlights the limitations of centralized execution engines and proposes a method for distributing workload among nodes to enhance process execution times and throughput. The approach also includes lightweight monitoring mechanisms and aims to support cloud-based deployments for dynamic scalability.
Decentralized enactment of bpel processes
- 1. ECRUITMENT SOLUTIONS (0)9751442511, 9750610101 #1, Ist Cross, Ist Main Road, Elango Nagar,Pondicherry-605 011. tech@ecruitments.com www.ecruitments.com Decentralized Enactment of BPEL Processes ABSTRACT: This article presents BPEL cube, 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 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 BPELcube and a comparison with centralized and clustered BPEL engine architectures demonstrate that the decentralized approach yields improved process execution times and throughput.
- 2. ECRUITMENT SOLUTIONS (0)9751442511, 9750610101 #1, Ist Cross, Ist Main Road, Elango Nagar,Pondicherry-605 011. tech@ecruitments.com www.ecruitments.com EXISTING SYSTEM: 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 BPELcube in order to organize an arbitrary number of nodes, which can then collaborate in the decentralized execution and monitoring of BPEL processes. THE Web Services Business Process Execution Language abbreviated toWS-BPEL or BPEL, is widely considered the de facto standard for the implementation of executable service-oriented business processes as compositions of Web services. The language specification defines a set of activities to support synchronous and asynchronous interactions between a process and its clients, as well as between a process and external Web services PROPOSED SYSTEM: To improve the throughput of the BPEL process execution infrastructure in the presence of multiple concurrent clients, a program partitioning technique has been proposed by Nanda et al.which splits a given BPEL process specification into an equivalent set of processes. The latter are then executed by different server nodes without the need of a centralized
- 3. ECRUITMENT SOLUTIONS (0)9751442511, 9750610101 #1, Ist Cross, Ist Main Road, Elango Nagar,Pondicherry-605 011. tech@ecruitments.com www.ecruitments.com coordinator. Similar approaches have also been proposed. Along the same lines, the use of a penalty based genetic algorithm to partition a given BPEL process and thereby allow decentralized execution was proposed. We are also interested in extending the proposed architecture to support Cloud-based deployment of the BPELcube engine. We anticipate that by moving BPELcube to the Cloud, we will be able to exploit elasticity capabilities for dynamically increasing or decreasing the hypercube dimension. This way, the BPELcube engine will be able to effectively and timely respond to workload changes. Finally, in terms of implementation, we will investigate the use of parallel query processing techniques to further enhance the performance of BPELcube nodes, in the presence of multiple concurrently running process instances. CONCLUSION: We presented a distributed architecture based on the hypercube P2P topology along with a set of algorithms that enable the decentralized execution of BPEL processes. Our approach targets towards the improvement of the average process execution times and the enhancement of the overall throughput of the execution infrastructure, in the presence of multiple long-running process instances that involve the exchange of large data. The presented algorithms support the decomposition of a given BPEL process and the subsequent assignment of the constituent activities and data variables to the available hypercube nodes. Execution is then performed in a completely decentralized manner without the existence of a central coordinator. Our distributed approach also provides a lightweight monitoring mechanism that does not intrude into the process execution, but
- 4. ECRUITMENT SOLUTIONS (0)9751442511, 9750610101 #1, Ist Cross, Ist Main Road, Elango Nagar,Pondicherry-605 011. tech@ecruitments.com www.ecruitments.com rather allows the retrieval of monitoring information from the hypercube in a seamless manner. We evaluated our approach in a series of experiments, and compared it with centralized and clustered architectures in terms of performance.