Advertisement

Scalable Workflow System Model Based on Mobile Agents

  • Jeong-Joon Yoo
  • Doheon Lee
  • Young-Ho Suh
  • Dong-Ik Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2132)

Abstract

A workflow system defines, creates and manages the execution of business workflows with workflow engines, which interpret workflow definitions, and interact with task performers. As most of non-trivial organizations have massive amount of workflows to process simultaneously, there is ever-increasing demands for better performance and scalability of workflow systems. This paper proposes a workflow system model based on mobile agents, so called Maximal Sequence model, as an alternative to conventional RPC-based and previous mobile agent-based (DartFlow) models. The proposed model segments a workflow definition into blocks, and assigning each of them to a mobile agent. We also construct three stochastic Petri net models of conventional RPC-based, DartFlow, and the Maximal Sequence model-based workflow systems to compare their performance and scalability. The stochastic Petri-net simulation results show that the proposed model outperforms the previous ones as well as comes up with better scalability when the numbers of workflow tasks and concurrent workflows are relatively large.

Keywords

Mobile Agent Maximal Sequence Agent Size Schedule Step Average Turnaround Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    WfMC: Workflow Management Coalition Terminology and Glossary-WfMC Specification, 1999.Google Scholar
  2. 2.
    Frank Leymann, and Dieter Roller: Business Process Management with FlowMark, Spring Compcon, Digest of Papers, pp 230–234, 1994.Google Scholar
  3. 3.
    Action Workflow website: http://www.actiontech.com/
  4. 4.
    FloWare website: http://www.plx.com/html/floware_scaleable_workflow.htmlGoogle Scholar
  5. 5.
    G. Alonso, C. Mohan, R. Gunthor, D. Agrawal, A. El Abbadi, and M. Kamath: Exotica/FMQM: A Persistent Message-Based Architecture for Distributed Workflow Management. In IFIP WG8.1 Working Conference on Information System Development for Decentralized Organizations, pp 1–18, 1995.Google Scholar
  6. 6.
    B. Nelson: Remote Procedure Call, Ph.D. Thesis, Carnegie-Mellon University, Pittsburgh, PA., CMU-CD-81–119.Google Scholar
  7. 7.
    Ting Cai, Peter A. Gloor, and Saurab Nog: DartFlow: A Workflow Management System on the Web using Transportable Agents, Technical report, Dartmouth College, 1997.Google Scholar
  8. 8.
    Colin G. Harrison, David M. Chess, and Aaron Kershenbaum: Mobile Agents: Are they a good idea?, Research Report, IBM Research Division, T.J.Watson Research Center, 1995.Google Scholar
  9. 9.
    D. F. Judge, B. Odgers, J. Shepherdson and Z. Li: Agent Enhanced Workflow, BT Technical Journal, 16:3, pp. 79–85, 1998.Google Scholar
  10. 10.
    K. Myers and P. Berry: Workflow Management Systems: An AI Perspective, Technical Report, Artificial Intelligence Center, SRI International, Menlo Park, CA, 1999.Google Scholar
  11. 11.
    D. D. Deavours, W. D. Obal II, M. A. Qureshi, W. H. Sanders, and A. P. A. van Moorsel.: UltraSAN Version 3 Overview: In Proceedings of International Workshop on Petri Nets and Performance Models, 1995.Google Scholar
  12. 12.
  13. 13.
    Manfred Dalmeijer, Eric Rietjens, Dieter Hammer, Ad Aerts, and Michiel Soede: A Reliable Mobile Agents Architecture, In Proceedings of the Int. Symposium on Object-Oriented Real-Time Distributed Computing, 1998.Google Scholar
  14. 14.
    Alberto Leon-Garcia: Probability and Random Processes for Electronical Engineering, nd Ed, Addison-Wesley Publishing Company, 1994.Google Scholar
  15. 15.
    Kwang-Hoon Kim, Su-Ki Paik, Dong-Su Han, Young-Chul Lew, and Moon-Ja Kim: An Instance-Active Transactional Workflow Architecture for Hanuri/TFlow, In proceedings of International Symposium on Database, Web and Cooperative Systems, 1999.Google Scholar
  16. 16.
    Donald Gross and Carl M. Harris: Fundamentals of Queueing Theory, 3rd Ed. John Wiley & Sons Inc., 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Jeong-Joon Yoo
    • 1
  • Doheon Lee
    • 2
  • Young-Ho Suh
    • 3
  • Dong-Ik Lee
    • 1
  1. 1.Department of Info. and CommKwang-Ju Institute of Science and TechnologyKorea (Republic of)
  2. 2.Department of Computer ScienceChonnam National UniversityKorea (Republic of)
  3. 3.Internet Service DepartmentElectronics and Telecommunications Research InstituteKorea (Republic of)

Personalised recommendations