skip to main content
10.1145/1137677.1137689acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
Article

SMDS: a top-down approach to self-management for dynamic collaboration systems

Published:21 May 2006Publication History

ABSTRACT

In this paper we present a distributed hierarchical system management concept for dynamic collaboration systems. Dynamic collaboration systems are composed of platforms containing resources; the platforms join forces to achieve a common mission. The automated system management concept discussed here is called the Self-Managing Distributed Systems(SMDS) concept.The SMDS concept distinguishes four segments of management: the Planning Segment, the Instantiation Segment, the Monitoring Segment and the Federation Segment. In this paper we will introduce these four segments, explain the functionality in each segment and how the segments interact. Furthermore, we will compare this SMDS concept with a service oriented approach.

References

  1. AFRL/IFSE. Jbi quick start guide. Technical report, AFRL, 2004. See http://www.rl.af.mil.]]Google ScholarGoogle Scholar
  2. D. S. Alberts. Network Centric Warfare. CCRP, 1999.]]Google ScholarGoogle Scholar
  3. K. Barnes, J. Cobb, and N. Ivezic. Crisis Management and Collaborative Computing: ORNL's Contributions. See http://www.ornl.gov.]]Google ScholarGoogle Scholar
  4. S. Basagni, M. Conti, S. Giordano, and I. StojmenoviĆ. Mobile Ad Hoc Networking. Wiley-IEEE Press, August 2004.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. G. Bieber and J. Carpenter. Openwings, a service-oriented component arcitecture for self-forming, self-healing network-centric systems. Technical report, Openwings, 2001. Available at http://www.openwings.org.]]Google ScholarGoogle Scholar
  6. C. Brinton, J. Krozel, B. Capozzi, and S. Atkins. "improved taxi prediction algorithms for the surface management system". 2002.]]Google ScholarGoogle Scholar
  7. J. de Jong. Fix the process not the bug. 2004. Available at http://combined.decis.nl.]]Google ScholarGoogle Scholar
  8. DECIS-Lab. COMBINED Systems Project. DECIS Lab. See http://combined.decis.nl.]]Google ScholarGoogle Scholar
  9. DECIS-Lab. ICIS Project. DECIS Lab. See http://www.icis.decis.nl.]]Google ScholarGoogle Scholar
  10. T. Erl. Service-Oriented Architecture, Concepts, Technology and Design. Prentice Hall, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. J. Ferber. Multi-Agent Systems, an Introduction to Distributed Artificial Intelligence. Addison Wesley, 1999.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. FIPA. Fipa agent management specification. Technical report, FIPA, 2004.]]Google ScholarGoogle Scholar
  13. M. Hannebauer. Autonomous Dynamic Reconfiguration in Multi-Agent Systems: Improving the Quality and Efficiency of Collaborative Problem Solving. In Lecture Notes in Computer Science, volume 2427. Springer-Verlag, Heidelberg, Germany, 2002.]]Google ScholarGoogle Scholar
  14. A. Helsinger and T. Wright. Cougaar: A robust configurable multi agent platform. In Proceedings of the IEEE Aerospace Conference 2005, (Big Sky Montana, March 5-12, 2005). IEEE, 2005.]]Google ScholarGoogle ScholarCross RefCross Ref
  15. J. Kephart and D. Chess. The vision of autonomic computing. IEEE Computer, 36(1):41--50., 2003.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. A. Krygiel. Behind the wizards curtain. CCRP, 1999.]]Google ScholarGoogle Scholar
  17. C. Larman. Applying UML and Patterns. Prentice Hall, 2nd ed edition, 2002.]]Google ScholarGoogle Scholar
  18. H. Levesque and J. N. P. R. Cohen. On acting together. Proc. of 8th National Conference on Artificial Intelligence, pages 94--99, 1990.]]Google ScholarGoogle Scholar
  19. T. Malone and K. Crowston. What is coordination theory and how can it help design cooperative work systems? In CSCW '90: Proceedings of the 1990 ACM conference on Computer-supported cooperative work, pages 357--370, New York, NY, USA, 1990. ACM Press.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. N. J. Nilsson. Principles of Artificial Intelligence. Springer Verlag, 1982.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. OMG. Unified Modeling Language: Superstructure. OMG, 2005.]]Google ScholarGoogle Scholar
  22. A. Omicini, F. Zambonelli, M. Klusch, and R. Tolksdorf, editors. Coordination of Internet Agents: Models, Technologies, and Applications. Springer Verlag, Heidelberg, Germany, 2001.]]Google ScholarGoogle Scholar
  23. J. Siegel. CORBA 3 Fundamentals and Programming. John Wiley & Sons, Inc., New York, NY, USA, 1999.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. C. van Aart. Organizational Principles for Multi-Agent Architectures. Whitestein Series in Software Agent Technologies. Birkhäuser, Basel, Switserland, 2005.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. J. B. van Veelen. Adaptive interfaces, a first investigation of selfmanaging systems. Technical report, Thales Nederland, 2004. See http://www.decis.nl.]]Google ScholarGoogle Scholar
  26. J. B. van Veelen. Self-managing distributed systems. Technical report, Thales Nederland, 2005. See http://www.decis.nl.]]Google ScholarGoogle Scholar
  27. M. Wooldridge. An introduction to Multi-Agent Systems. John Wiley and Sons, 1992.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. SMDS: a top-down approach to self-management for dynamic collaboration systems

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SEAMS '06: Proceedings of the 2006 international workshop on Self-adaptation and self-managing systems
          May 2006
          102 pages
          ISBN:1595934030
          DOI:10.1145/1137677

          Copyright © 2006 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 21 May 2006

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • Article

          Acceptance Rates

          Overall Acceptance Rate17of31submissions,55%

          Upcoming Conference

          ICSE 2025
        • Article Metrics

          • Downloads (Last 12 months)1
          • Downloads (Last 6 weeks)0

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader