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Combining state and model-based approaches for mobile agent load balancing

Published:09 March 2003Publication History

ABSTRACT

An approach for dynamic load balancing of mobile agents is described. We demonstrate this approach for a multi-agent system operating on an active digital library composed of multi-spectral images of the Earth, as part of the Synthetic Aperture Radar Atlas (SARA)[25]. In the proposed architecture specialized stationary agents are used to gather system state information and make decisions on the distribution of mobile agents among the servers. Our approach is based on a combination of a state and model-based approaches to load balancing.

References

  1. Backschat, M., Pfaffinger, A., Zenger, C. Economic-based dynamic load distribution in large workstation networks. In proceedings of the 2nd International Euro-Par Conference, volume 2, pp. 631--634, Lyon, France, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Cabrera, L., F. The influence of workload on balancing strategies. In USENIX summer conference, pp. 446--58, 1986.Google ScholarGoogle Scholar
  3. Chavez, A., Moukas, A., Maes, P. Challenger: A multi-agent system for distributed resource allocation. In proceedings of the First International Conference on Autonomous Agents AA97, ACM Press, Marina del Ray, CA, USA, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Eager, D., L., Lazowska, E., D., Zahorjan, J. Adaptive load sharing in homogeneous distributed systems. IEEE Trans on Software Engineering, vol SE-12, pp. 662--675, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Erfurth, C., Braun, P., Rossak, W., Migration intelligence for mobile agents. Artificial Intelligence and the Simulation of Behaviour (AISB) Symposium on Software mobility and adaptive behaviour. University of York, United Kingdom, pp. 81--88, 2001.Google ScholarGoogle Scholar
  6. Frank, M. O. C. E. A. N. The open computation exchange and arbitration network, 2000. http://www.cise.ufl.edu/~mpf/ocean.Google ScholarGoogle Scholar
  7. FLASH - Flexible Agent System for Heterogeneous Cluster. http://www.iti.mu-luebeck.de/Research/PC/Flash/.Google ScholarGoogle Scholar
  8. Georgousopoulos, C., Rana, O., F. An approach to conforming a MAS into a FIPA-compliant system. In First International Joint Conference on Autonomous Agents and Multi-Agent Systems - AAMAS 2002, ACM ISBN 1-58113-480-0, pp. 968--975, Italy, Bologna, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Ghanea-Hercock, R., Collis, J., C., Ndumu, D., T. Cooperating mobile agents for distributed parallel processing. In proceedings of the Third International Conference on Autonomous Agents AA99, ACM press, Mineapolis, USA, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Gomoluch, J., Schroeder, M. Information agents on the move: A survey on load-balancing with mobile agents. In Software Focus, Vol. 2, no. 2, Wiley, 2001.Google ScholarGoogle Scholar
  11. Gonne, M., Grewe, C., Pals, H. Monitoring of Mobile Agents in Large Cluster Systems. Published in IEEE International Symposium on Network Computing and Applications, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Harchol-Balter, M., Downey, A., B. Exploiting process lifetime distributions for dynamic load balancing. ACM Transactions on Computer Systems, 15(3):253--85, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. http://www.cs.cf.ac.uk/Digital-Library/.Google ScholarGoogle Scholar
  14. Keren, A., Barak, A. Adaptive placement of parallel java agents in a scalable computing cluster. In proceedings of the Workshop on Java for High Performance Network Computing, ACM Press, Stanford University, Palo Alto, CA, USA, 1998.Google ScholarGoogle ScholarCross RefCross Ref
  15. Malone, T., W., Fikes, R., E., Grant, K., R., and Howard, M., T. Enterprise: A market-like Task Scheduler for Distributed Computing Environments. In: The Ecology of Computation. Ed. Huberman, B. A. Elsevier, Holland, 1988.Google ScholarGoogle Scholar
  16. Obeloeer, W., Grewe, C. Load management with mobile agents. In proceedings of the 24th EUROMICRO Conference, IEEE, pp. 1005--1012, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Sandholm, T. Distributed rational decision making. In the textbook Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, Weiss, G. (ed.), MIT press, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Tanenbaum, Andrew, S. Modern operating systems. Englewood Cliffs, New Jersy: Prentice-Hall, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Voyager 4.01, Recursion Software, Inc. http://www.recursionsw.com/osi.asp.Google ScholarGoogle Scholar
  20. Voyager 4.01 ORB developer guide, chapter 'Voyager Basics', Recursion Software, Inc. http://www.recursionsw.com/osi.asp.Google ScholarGoogle Scholar
  21. Voyager 4.01 ORB developer guide, chapter 'Advanced Messaging', Recursion Software, Inc. http://www.recursionsw.com/osi.asp.Google ScholarGoogle Scholar
  22. Waldspurger, C. A., Hogg, T., Huberman, B. A., Kephart, J. O., Stornetta, W. S. Spawn: a distributed computational economy. Transactions on Software Engineering, 18(2):103--117, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Williams, R. D., Sears, B., A High-Performance Active Digital Library, Parallel Computing. Special issue on Metacomputing, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Xu, C., Z., Wims, B. A mobile agent based push methodology for global parallel computing. In Proceedings of the First International Symposium on Agent Systems and Applications (ASA'99) / Third International Symposium on Mobile Agents (MA'99), IEEE, 1999.Google ScholarGoogle Scholar
  25. Yang, Y., Rana, O. F., Walker, D. W., Georgousopoulos, C., Aloisio, G., Williams, R. D. Agent based data management in Digital Libraries Remote-Sensing Archive. Published in Parallel Computing Journal, Elsevier Science, Vol. 28, issue 5, pp. 773--792, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Conferences
    SAC '03: Proceedings of the 2003 ACM symposium on Applied computing
    March 2003
    1268 pages
    ISBN:1581136242
    DOI:10.1145/952532

    Copyright © 2003 ACM

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    Publication History

    • Published: 9 March 2003

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