Agent-Based Distance Vector Routing

  • Kaizar A. Amin
  • John T. Mayes
  • Armin R. Mikler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2164)


Mobile Agents are being proposed for an increasing variety of applications. Distance Vector Routing (DVR) is an example of one application that can benefit from an agent-based approach. DVR algorithms, such as RIP, have been shown to cause considerable network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. However, in an agent-based solution, the number of messages is bounded by the number of agents in the system. In this paper, we present an agent-based solution to DVR. In addition, we will describe agent migration strategies that improve the performance of the route discovery process, namely Random Walk and Structured Walk.


Mobile Agent Adjacent Node Route Discovery Migration Strategy Route Discovery Process 
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.


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  1. 1.
    G. S. Malkin and M. E. Steenstrup. Distance-vector routing. In M. E. Steenstrup, editor, Routing in Communications Networks, pages 83–98. Prentice Hall, 1995.Google Scholar
  2. 2.
    G. Di Caro and M. Dorigo, AntNet: Distributed stigmergetic control for communications networks, Technical Report 98-01, IRIDIA, Universite Libre de Bruxelles, 1998, (Accepted for publication in the Journal of Artificial Intelligence Research (JAIR)).Google Scholar
  3. 3.
    D. P. Bertsekas and R. G. Gallaher, Data Networks, Prentice-Hall, Englewood Cliffs, N.J., 1987.Google Scholar
  4. 4.
    J. F. Kurose and K. W. Ross. Computer Networking, A Top Down Approach Featuring the Internet, Addison-Wesley, 2001.Google Scholar
  5. 5.
  6. 6.
    N. Minar, K. H. Kramer and P. Maes, Cooperating Mobile Agents for Mapping Networks, Proceedings of the First Hungarian National Conference on Agent Based Computing.1998.Google Scholar
  7. 7.
    N. Minar, K. H. Kramer and P. Maes, Cooperating Mobile Agents for Dynamic Network Routing, Software Agents for Future Communications Systems, Springer-Verlag, 1999, ISBN 3-540-65578-6.Google Scholar
  8. 8.
    R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.Google Scholar
  9. 9.
    The Mechanics of Routing Protocols, CISCO Press.
  10. 10.
    M. Bui, S. K. Das, A. K. Datta and D. T. Nguyen, Randomized Mobile Agent Based Routing in Wireless Networks Google Scholar
  11. 11.
    A. Fugetta, G. P. Picco, G. Vigna, Understanding Code Mobility, IEEE Trans. Softw. Eng. 24(5), 342–361, 1998CrossRefGoogle Scholar
  12. 12.
    J. M. Bradshaw Software Agents. AAAI Press, Menlo Park, California/The MIT Press.Google Scholar
  13. 13.
    A. R. Mikler, J. S. K. Wong and V. G. Honovar, An Object-Oriented Approach to Simulate Large Communication Networks. The Journal of Systems and Software. Volume 40, No.2. pp.61–73.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Kaizar A. Amin
    • 1
  • John T. Mayes
    • 1
  • Armin R. Mikler
    • 1
  1. 1.Department of Computer ScienceUniversity of North TexasDentonUSA

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