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Volume 25 Issue 6
October  2010
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Yan-Bo Han, Jun-Yi Sun, Gui-Ling Wang, Hou-Fu Li. A Cloud-Based BPM Architecture with User-End Distribution of Non-Compute-Intensive Activities and Sensitive Data[J]. Journal of Computer Science and Technology, 2010, 25(6): 1157-1167. DOI: 10.1007/s11390-010-1092-5
Citation: Yan-Bo Han, Jun-Yi Sun, Gui-Ling Wang, Hou-Fu Li. A Cloud-Based BPM Architecture with User-End Distribution of Non-Compute-Intensive Activities and Sensitive Data[J]. Journal of Computer Science and Technology, 2010, 25(6): 1157-1167. DOI: 10.1007/s11390-010-1092-5
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A Cloud-Based BPM Architecture with User-End Distribution of Non-Compute-Intensive Activities and Sensitive Data

  • 1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Funds: Supported by the National Basic Research 973 Program of China under Grant No. 2007CB310805, the National Natural Science Foundation of China under Grant Nos. 90412010, 60970131 and 60903048, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01A106 and the Beijing Natural Science Foundation under Grant No. 4092046.
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  • Author Bio:

    Yan-Bo Han is a professor at the Institute of Computing Technologyand the Graduate University of Chinese Academy of Sciences in Beijing,China. He also serves as the director of the Institute of ServiceEngineering, Shandong University of Science and Technology in Qingdao,China. His current research interests include Internet computing,services interoperability and composition, dependable distributedsystems, business process collaboration and management.

    Jun-Yi Sun received his B.S. degree in electronic engineeringfrom Huazhong Normal University, and B.S degree in computer sciencefrom Huazhong University of Science and Technology in 2006. He is aPh.D. candidate in Graduate School of the Chinese Academy of Sciences.His current research interests include workflow scheduling andcloud-based BPM.

    Gui-Ling Wang is currently an assistant professor in theInstitute of Computing Technology, Chinese Academy of Sciences (ICT,CAS). She received her Ph.D. degree in computer science from TsinghuaUniversity in 2007. Her research interests include servicescomposition, information integration and Web Mashup technologies.

    Hou-Fu Li is an assistant professor at the Institute of ComputingTechnology.He received his Ph.D. degree in computer science from the GraduateUniversity of Chinese Academy of Sciences in 2008. His researchinterests include service- and event-based business process managementand collaboration technologies, and dependable and high productiveInternet-based operating system.

  • Received Date: July 14, 2009
  • Revised Date: January 28, 2010
  • Published Date: October 31, 2010
    Abstract
  • While cloud-based BPM (Business Process Management) shows potentials of inherent scalability and expenditure reduction, such issues as user autonomy, privacy protection and efficiency have popped up as major concerns. Users may have their own rudimentary or even full-fledged BPM systems, which may be embodied by local EAI systems, at their end, but still intend to make use of cloud-side infrastructure services and BPM capabilities, which may appear as PaaS (Platform-as-a-Service) services, at the same time. A whole business process may contain a number of non-compute-intensive activities, for which cloud computing is over-provision. Moreover, some users fear data leakage and loss of privacy if their sensitive data is processed in the cloud. This paper proposes and analyzes a novel architecture of cloud-based BPM, which supports user-end distribution of non-compute-intensive activities and sensitive data. An approach to optimal distribution of activities and data for synthetically utilizing both user-end and cloud-side resources is discussed. Experimental results show that with the help of suitable distribution schemes, data privacy can be satisfactorily protected, and resources on both sides can be utilized at lower cost.
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