A Cluster-Based Approach for Disturbed, Spatialized, Distributed Information Gathering Systems

  • Quang-Anh Nguyen Vu
  • Benoit Gaudou
  • Richard Canal
  • Salima Hassas
  • Frédéric Armetta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7057)

Abstract

In a distributed spatialized information collecting system managed by a swarm of agents, where some are supposed disturbed, the maintenance of the system coherence and cooperation between reliable elements is a challenge. This paper tackles the problem of finding an efficient mechanism to ensure the coherence of the system and to optimize system performance. The main contribution of this paper consists of two major steps: (i) use trust-based mechanism to ensure the coherence and the robustness of the system; (ii) allow reliable elements to create dynamic clusters based on trust. We propose two different organizations in order to manage these issues and show how they must interact: a social one in which each agent maintains a TrustSet to estimate trust on others; a spacial one in which reliable elements are grouped in an “ad hoc type” network to improve cooperation between themselves.

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References

  1. 1.
    Nguyen Vu, Q.A., Gaudou, B., Canal, R., Hassas, S., Armetta, F.: Stratégie de communication dans un systéme de collecte d’information á base d’agents perturbés. In: Journées Francophones des Systémes Multi-Agents (JFSMA), France, pp. 207–217 (2009)Google Scholar
  2. 2.
    Nguyen Vu, Q.A., Gaudou, B., Canal, R., Hassas, S., Armetta, F.: TrustSets - Using trust to detect deceitful agents in a distributed information collecting system. In: 2010 IEEE-RIVF International Conference on Computing and Communication Technologies (2010)Google Scholar
  3. 3.
    Horling, B., Lesser, V.: A survey of multi-agent organizational paradigms. The Knowledge Engineering Review 19(4), 281–316 (2004)CrossRefGoogle Scholar
  4. 4.
    Parker, L.E., Reardon, C.M., Choxi, H., Bolden, C.: Using critical junctures and environmentally-dependent information for management of tightly-coupled cooperation in heterogeneous robot teams. In: ICRA 2009: Proceedings of the, IEEE International Conference on Robotics and Automation, pp. 2872–2879. IEEE Press, Piscataway (2009)Google Scholar
  5. 5.
    Drira, K., Kheddouci, H., Tabbane, N.: Virtual dynamic topology for routing in mobile ad hoc networks. In: Proceedings of the International Conference on Late Advances in Networks ICLAN 2006, France, pp. 129–134 (2006)Google Scholar
  6. 6.
    Perkins, C.E.: Ad Hoc Networking. Addison-Wesley Professional (2008)Google Scholar
  7. 7.
    Haddad, M., Kheddouci, H.: A survey on graph based service discovery approaches for ad hoc networks. International Transactions on Systems Science and Applications (2007)Google Scholar
  8. 8.
    Le, V.T., Bouraqadi, N., Stinckwich, S., Moraru, V., Doniec, A.: Making networked robots connectivity-aware. In: ICRA 2009: Proceedings of the 2009 IEEE International Conference on Robotics and Automation, pp. 1835–1840. IEEE Press, Piscataway (2009)Google Scholar
  9. 9.
    Maclennan, B.: Synthetic ethology: An approach to the study of communication, pp. 631–658. Addison-Wesley (1991)Google Scholar
  10. 10.
    Balch, T., Ronald, Arkin, C.: Communication in reactive multiagent robotic systems. Autonomous Robots 1, 27–52 (1994)CrossRefGoogle Scholar
  11. 11.
    Basagni, S.: Distributed clustering for ad hoc networks. In: ISPAN 1999: Proceedings of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks, p. 310. IEEE Computer Society, Washington, DC, USA (1999)Google Scholar
  12. 12.
    Nguyen Vu, Q.A., Gaudou, B., Canal, R., Hassas, S., Armetta, F., Stinckwich, S.: Using trust and cluster organisation to improve robot swarm mapping. In: ROSIN 2010: Workshop on Robots and Sensors integration in Future Rescue INformation System (2010) (to appear)Google Scholar
  13. 13.
    Amouroux, E., Quang, C., Boucher, A., Drogoul, A.: GAMA: an Environment for Implementing and Running Spatially Explicit Multi-Agent Simulations. In: Ghose, A., Governatori, G., Sadananda, R. (eds.) PRIMA 2007. LNCS, vol. 5044, pp. 359–371. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. 14.
    Hassas, S.: Systèmes complexes à base de multi-agents situès. Universitè Claude Bernard-Lyon 1, Mèmoire d’habilitation à diriger les recherches (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Quang-Anh Nguyen Vu
    • 1
  • Benoit Gaudou
    • 2
  • Richard Canal
    • 1
  • Salima Hassas
    • 3
  • Frédéric Armetta
    • 3
  1. 1.UMI 209 UMMISCOInstitut de la Francophonie pour l’Informatique (IFI)HanoiVietnam
  2. 2.UMR CNRS 5505, Institut de Recherche en Informatique de ToulouseUniversité Paul Sabatier Toulouse 3France
  3. 3.Laboratoire LIESPUniversité Claude Bernard Lyon 1France

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