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Distributed Fault Location in Networks Using Learning Mobile Agents

  • Tony White
  • Bernard Pagurek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1733)

Abstract

This paper describes how multiple interacting swarms of adaptive mobile agents can be used to locate faults in networks. The paper proposes the use of distributed problem solving using learning mobile agents for fault finding. The paper uses a recently described architectural description for an agent that is biologically inspired and proposes chemical interaction as the principal mechanism for inter-swarm communication. Agents have behavior that is inspired by the foraging activities of ants, with each agent capable of simple actions; global knowledge is not assumed. The creation of chemical trails is proposed as the primary mechanism used in distributed problem solving arising from the self-organization of swarms of agents. Fault location is achieved as a consequence of agents moving through the network, sensing, acting upon sensed information, and subsequently modifying the chemical environment that they inhabit. Elements of a mobile code framework that is being used to support this research, and the mechanisms used for agent mobility within the network environment, are described.

Keywords

Mobile Agent Fault Location Network Management Problem Agent Swarm Intelligence 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Tony White
    • 1
  • Bernard Pagurek
    • 1
  1. 1.Systems and Computer EngineeringCarleton UniversityOttawaCanada K1S 5B6

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