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Physarum-Inspired Self-biased Walkers for Distributed Clustering

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Principles of Distributed Systems (OPODIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7702))

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Abstract

We propose a distributed scheme to compute distance-based clusters. We first present a mechanism based on the flow of distributed tokens called walkers, circulating randomly between a source and a sink to compute a shortest path. Each time a walker takes an edge, it reinforces the probability that subsequent walkers take it. This mechanism is a discrete emulation of the slime mould (Physarum polycephalum) dynamics presented in [16]: each node observes the flow of walkers going through each adjacent edge and uses this flow to compute the probabilities with which it sends the walkers through each edge. Then, based on this mechanism, we show how several sources compute a shortest path DAG to a given sink. Finally, given some clusterheads acting like sinks, we show that this process converges to distance-based clusters (i.e. nodes join the clusterhead to which they are closest) with shortest-path DAGs. The algorithm is designed with a special focus on dynamic networks: the flow locally adapts to the appearance and disappearance of links and nodes, including clusterheads.

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References

  1. Amis, A.D., Prakash, R., Vuong, T.H.P., Huynh, D.T.: Max-min d-cluster formation in wireless ad hoc networks. In: Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, IEEE INFOCOM 2000, pp. 32–41 (2000)

    Google Scholar 

  2. Basagni, S.: Distributed clustering for ad hoc networks. In: International Symposium on Parallel Architectures, Algorithms and Networks, ISPAN, pp. 310–315 (1999)

    Google Scholar 

  3. Bernard, T., Bui, A., Pilard, L., Sohier, D.: Distributed Clustering Algorithm for Large-Scale Dynamic Networks. International Journal of Cluster Computing (2010), doi:10.1007/s10586-011-0153-z

    Google Scholar 

  4. Bui, A., Clavière, S., Datta, A.K., Larmore, L.L., Sohier, D.: Self-stabilizing Hierarchical Construction of Bounded Size Clusters. In: Kosowski, A., Yamashita, M. (eds.) SIROCCO 2011. LNCS, vol. 6796, pp. 54–65. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Bui, A., Kudireti, A., Sohier, D.: An adaptive random walks based distributed clustering algorithm. International Journal of Foundations of Computer Science 23(4), 802–830 (2012)

    Article  Google Scholar 

  6. Datta, A.K., Larmore, L.L., Vemula, P.: A self-stabilizing O(k)-time k-clustering algorithm. The Computer Journal 53(3), 342–350 (2010)

    Article  Google Scholar 

  7. Dolev, S., Tzachar, N.: Empire of colonies: Self-stabilizing and self-organizing distributing algorithm. Theoretical Computer Science 410, 514–532 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  8. Ephremides, A., Wieselthier, J.E., Baker, D.J.: A design concept for reliable mobile radio networks with frequency hopping signaling. Proceedings of the IEEE, 56–73 (1987)

    Google Scholar 

  9. Johnen, C., Nguyen, L.: Robust self-stabilizing weight-based clustering algorithm. Theoretical Computer Science 410(6-7), 581–594 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  10. Sucec, J., Marsic, I.: Location management handoff overhead in hierarchically organized mobile ad hoc networks. In: International Parallel and Distributed Processing Symposium, IPDPS, vol. 2, p. 198, 0194 (2002)

    Google Scholar 

  11. Thaler, D.G., Ravishankar, C.V.: Distributed top-down hierarchy construction. In: Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies, IEEE INFOCOM 1998, vol. 2, pp. 693–701 (1998)

    Google Scholar 

  12. Yang, S.-J., Chou, H.-C.: Design Issues and Performance Analysis of Location-Aided Hierarchical Cluster Routing on the MANET. In: Communications and Mobile Computing, CMC, pp. 26–31 (2009)

    Google Scholar 

  13. Bellman, R.: Dynamic Programming. Princeton University Press, Dover (1957)

    MATH  Google Scholar 

  14. Rabat, C.: Dasor, a Discret Events Simulation Library for Grid and Peer-to-peer Simulators. Studia Informatica Universalis 7 (2009)

    Google Scholar 

  15. Adamatzky, A., de Oliveira, P.P.B.: Brazilian highways from slime mold’s point of view. Kybernetes 40(9), 1373–1394 (2011)

    Article  Google Scholar 

  16. Bonifaci, V., Mehlhorn, K., Varma, G.: Physarum can compute shortest paths. In: Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 233–240 (2012)

    Google Scholar 

  17. Doyle, P.G., Snell, L.J.: Random Walks and Electrical Networks. Mathematical Association of America (December 1984)

    Google Scholar 

  18. Gkantsidis, C., Mihail, M., Saberi, A.: Random walks in peer-to-peer networks: Algorithms and evaluation. Performance Evaluation 63(3), 241–263 (2006)

    Article  Google Scholar 

  19. Ito, K., Johansson, A., Nakagaki, T., Tero, A.: Convergence properties for the physarum solver. arXiv:1101.5249 (January 2011)

    Google Scholar 

  20. Johannson, A., Zou, J.: A Slime Mold Solver for Linear Programming Problems. In: Cooper, S.B., Dawar, A., Löwe, B. (eds.) CiE 2012. LNCS, vol. 7318, pp. 344–354. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  21. Lenzen, C., Suomela, J., Wattenhofer, R.: Local Algorithms: Self-stabilization on Speed. In: Guerraoui, R., Petit, F. (eds.) SSS 2009. LNCS, vol. 5873, pp. 17–34. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  22. Li, K., Torres, C., Thomas, K., Rossi, L., Shen, C.-C.: Slime mold inspired routing protocols for wireless sensor networks. Swarm Intelligence 5(3), 183–223 (2011)

    Article  Google Scholar 

  23. Miyaji, T.: Mathematical analysis to an adaptive network of the plasmodium system. Hokkaido Mathematical Journal 36(2), 445–465 (2007); Mathematical Reviews number (MathSciNet): MR2347434

    Google Scholar 

  24. Miyaji, T., Onishi, I.: Physarum can solve the shortest path problem on riemannian surface mathematically rigourously. International Journal of Pure and Applied Mathematics 47(3) (2008)

    Google Scholar 

  25. Nakagaki, T., Tero, A., Kobayashi, R., Onishi, I., Miyaji, T.: Computational ability of cells based on cell dynamics and adaptability. New Generation Computing 27(1), 57–81 (2008)

    Article  Google Scholar 

  26. Tero, A., Takagi, S., Saigusa, T., Ito, K., Bebber, D.P., Fricker, M.D., Yumiki, K., Kobayashi, R., Nakagaki, T.: Rules for biologically inspired adaptive network design. Science 327(5964), 439–442 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  27. Wagner, D., Wattenhofer, R. (eds.): Algorithms for Sensor and Ad Hoc Networks. LNCS, vol. 4621. Springer, Heidelberg (2007)

    Google Scholar 

  28. Georgiadis, G., Papatriantafilou, M.: A Least-Resistance Path in Reasoning about Unstructured Overlay Networks. In: Sips, H., Epema, D., Lin, H.-X. (eds.) Euro-Par 2009. LNCS, vol. 5704, pp. 483–497. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  29. Bui, A., Sohier, D.: How to compute times of random walks based distributed algorithms. Fundamenta Informaticae 80(4), 363–378 (2007)

    MathSciNet  MATH  Google Scholar 

  30. Georgiadis, G., Papatriantafilou, M.: Physarum-inspired self-biased walkers for distributed clustering, Chalmers University of Technology, TR-2012:08 (June 2012)

    Google Scholar 

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Sohier, D., Georgiadis, G., Clavière, S., Papatriantafilou, M., Bui, A. (2012). Physarum-Inspired Self-biased Walkers for Distributed Clustering. In: Baldoni, R., Flocchini, P., Binoy, R. (eds) Principles of Distributed Systems. OPODIS 2012. Lecture Notes in Computer Science, vol 7702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35476-2_22

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  • DOI: https://doi.org/10.1007/978-3-642-35476-2_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35475-5

  • Online ISBN: 978-3-642-35476-2

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