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Self-organizing Approaches for Large-Scale Spray Multiagent Systems

  • Marco Mamei
  • Franco Zambonelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3914)

Abstract

Large-scale multiagent systems will be the key software technology driving several future application scenarios. We envision a future in which clouds of microcomputers can be sprayed in an environment to provide, by spontaneously networking with each other, an endlessly range of futuristic applications. Beside this vision, similar kind of large-scale “spray” multiagent systems will be employed in several other scenarios ranging from ad-hoc networks of embedded and mobile devices to worldwide distributed computing. All of these scenarios present strong commonalities from the application development point of view, and new approaches and methodologies will be likely to apply, to some extent, to all of them. In particular, we argue that the issues related to the design and development of such spray multiagent systems call for novel approaches exploiting self-organization as first-class tools. With this regard, we survey a number of research projects around the world trying to apply self-organization to large-scale multiagent systems. Finally, we attempt at defining a rough research agenda that – in the long run – should integrate these ideas to develop a general and more assessed methodology for large-scale spray multiagent systems crosscutting several application domains.

Keywords

Sensor Network Multiagent System Reverse Engineering Overlay Network Medium Scale 
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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References

  1. 1.
    Albert, R., Jeong, H., Barabasi, A.: Error and Attack Tolerance of Complex Networks. Nature 406, 378–382 (2000)CrossRefGoogle Scholar
  2. 2.
    Babaoglu, O., Meling, H., Montresor, A.: Anthill: A Framework for the Development of Agent-Based Peer-to-Peer Systems. In: International Conference on Distributed Computing Systems, Vienna (A) (2002)Google Scholar
  3. 3.
    Berlin, A.A., Gabriel, K.J.: Distributed MEMS: New Challenges for Computation. IEEE Computing in Science and Engineering 4(1), 12–16 (1997)CrossRefGoogle Scholar
  4. 4.
    Bernon, C., Gleizes, M.P., Peyruqueou, S., Picard, G.: ADELFE: a Methodology for Adaptive Multi-Agent Systems Engineering. In: Petta, P., Tolksdorf, R., Zambonelli, F. (eds.) ESAW 2002. LNCS (LNAI), vol. 2577, pp. 156–169. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence. Oxford University Press, Oxford (1999)MATHGoogle Scholar
  6. 6.
    Braginsky, D., Estrin, D.: Rumor Routing Algorithm For Sensor Networks. In: 1st Workshop on Sensor Networks and Applications, WSNA (2002)Google Scholar
  7. 7.
    Broch, J., Maltz, D., Johnson, D., Hu, Y., Jetcheva, J.: A Perfomance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols. In: ACM/IEEE Conference on Mobile Computing and Networking. ACM Press, Dallas (1998)Google Scholar
  8. 8.
    Catterall, E., Van Laerhoven, K., Strohbach, M.: Self-Organization in Ad-Hoc Sensor Networks: An Empirical Study. In: Proc. of Artificial Life VIII, Sydney, Australia. MIT Press, Cambridge (2002)Google Scholar
  9. 9.
    Crichton, M.: Prey: a Novel, HarperCollins (2002)Google Scholar
  10. 10.
    Estrin, D., Culler, D., Pister, K., Sukjatme, G.: Connecting the Physical World with Pervasive Networks. IEEE Pervasive Computing 1(1), 59–69 (2002)CrossRefGoogle Scholar
  11. 11.
    George, J.P., Edmonds, B., Glize, P.: Making self-organizing adaptive multi-agent systems work. To appear in Methodologies and Software Engineering for Agent Systems. Kluwer, Dordrecht (2004)Google Scholar
  12. 12.
    Imielinski, T., Goel, S.: Dataspace - querying and monitoring deeply networked collections in physical space. IEEE Personal Communications Magazine, 4–9 (2000)Google Scholar
  13. 13.
    Jacob, C.: Illustrating Evolutionary Computation with Mathematica. Morgan Kauffman Publisher, San Francisco (2001)Google Scholar
  14. 14.
    Kennedy, J., Eberhart, R.: Swarm Intelligence. Morgan Kauffman Publisher, San Francisco (2001)Google Scholar
  15. 15.
    Kephart, J., Chess, D.M.: The Vision of Autonomic Computing. IEEE Computer 36(1), 41–50 (2003)CrossRefGoogle Scholar
  16. 16.
    Mamei, M., Zambonelli, F.: Programming Pervasive and Mobile Computing Applications with the TOTA Middleware. In: 2nd IEEE Conference on Pervasive Computing and Communications, Orlando, FL (2004)Google Scholar
  17. 17.
    Mamei, M., Zambonelli, F., Leonardi, L.: Co-Fields: a Physically Inspired Approach to Distributed Motion Coordination. IEEE Pervasive Computing, 3 (2), 52–60Google Scholar
  18. 18.
    Menezes, R., Tolksdorf, R.: SwarmLinda: a New Approach to Scalable Linda Systems based on Swarms. In: 16th ACM Symposium on Applied Computing, Melbourne, FL (2003)Google Scholar
  19. 19.
    Moukas, A., Maes, P.: Amalthaea: An Evolving Multi-Agent Information Filtering and Discovery System for the WWW. Journal of Autonomous Agents and Multi-Agent Systems 1(1), 59–88 (1998)CrossRefGoogle Scholar
  20. 20.
    Nagpal, R., Kondacs, A., Chang, C.: Programming Methodology for Biologically-Inspired Self-Assembling Systems. In: AAAI Spring Symposium on Computational Synthesis (2003)Google Scholar
  21. 21.
    Nagpal, R., Shrobe, H., Bachrach, J.: Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 333–348. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  22. 22.
    Nick, Z., Themis, P.: Web Search Using a Genetic Algorithm. IEEE Internet Computing 5(3), 18–26 (2001)CrossRefGoogle Scholar
  23. 23.
    Parunak, V., Brueckner, S., Sauter, J.: Digital Pheromones for Coordination of Unmanned Vehicles. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 246–263. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  24. 24.
    Parunak, V., Bruekner, S., Sauter, J.: ERIM’s Approach to Fine-Grained Agents. In: NASA/JPL Workshop on Radical Agent Concepts, Greenbelt (MD) (January 2002)Google Scholar
  25. 25.
    Patterson, D., Liao, L., Fox, D., Kautz, H.: Inferring high-level behavior from low-level sensors. In: Dey, A.K., Schmidt, A., McCarthy, J.F. (eds.) UbiComp 2003. LNCS, vol. 2864, pp. 73–89. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  26. 26.
    Payton, D., Daily, M., Estowski, R., Howard, M., Lee, C.: Pheromone Robotics. Autonoumous Robots 11(3), 319–324 (2001)CrossRefMATHGoogle Scholar
  27. 27.
    Philipose, M., Fishkin, K., Perkowitz, M., Patterson, D., Fox, D., Kautz, H., Hahnel, D.: Inferring Activities from Interactions with Objects. IEEE Pervasive Computing 3(4), 50–57 (2004)CrossRefGoogle Scholar
  28. 28.
    Ratsanamy, S., Francis, P., Handley, M., Karp, R.: A Scalable Content-Addressable Network. In: ACM SIGCOMM Conference 2001 (2001)Google Scholar
  29. 29.
    Ripeani, M., Iamnitchi, A., Foster, I.: Mapping the Gnutella Network. IEEE Internet Computing 6(1), 50–57 (2002)CrossRefGoogle Scholar
  30. 30.
    Roman, M., et al.: Gaia: A Middleware Infrastructure for Active Spaces. IEEE Pervasive Computing 1(4), 74–83 (2002)CrossRefGoogle Scholar
  31. 31.
    Rowstron, A., Druschel, P.: Pastry: Scalable, Decentralized Object Location and Routing for Large-Scale Peer-to-Peer Systems. In: Guerraoui, R. (ed.) Middleware 2001. LNCS, vol. 2218, p. 329. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  32. 32.
    Shen, W., Salemi, B., Will, P.: Hormone-Inspired Adaptive Communication for Self-Reconfigurable Robots. IEEE Transaction on Robotics and Automation 18(5), 1–12 (2002)Google Scholar
  33. 33.
    Simic, S.: A Learning-Theory Approach to Sensor Network. IEEE Pervasive Computing 2(4), 44–49 (2003)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Stoy, K., Nagpal, R.: Self-Reconfiguration Using Directed Growth. In: 7th International Symposium on Distributed Autonomous Robotic Systems, Toulouse (F) (2004)Google Scholar
  35. 35.
    Vasirani, M., Mamei, M., Zambonelli, F.: Morphogenesis of Cooperative Mobile Robots with Minimal Capabilities. Presented at the 1st European Workshop on Multiagent Systems, Oxford, UK (2003)Google Scholar
  36. 36.
    Zambonelli, F., Mamei, M.: The Cloak of Invisibility: Challenges and Applications. IEEE Pervasive Computing 1(4), 62–70 (2002)CrossRefGoogle Scholar
  37. 37.
    Zambonelli, F., Mamei, M., Roli, A.: What Can Cellular Automata Tell Us About the Behaviour of Large Multi-Agent Systems? In: Garcia, A., et al. (eds.) SELMAS 2002. LNCS, vol. 2603, pp. 216–231. Springer, Heidelberg (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marco Mamei
    • 1
  • Franco Zambonelli
    • 1
  1. 1.Dipartimento di Scienze e Metodi dell’IngegneriaUniversità di Modena e Reggio EmiliaItaly

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