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Combining Uniform and Heuristic Search: Solving DSSSP with Restricted Knowledge of Graph Topology

  • Sandro Castronovo
  • Björn Kunz
  • Christian Müller
Part of the Communications in Computer and Information Science book series (CCIS, volume 358)

Abstract

Shortest-path problems on graphs have been studied in depth in Artificial Intelligence and Computer Science. Search on dynamic graphs, i.e. graphs that can change their layout while searching, receives plenty of attention today – mostly in the planning domain. Approaches often assume global knowledge on the dynamic graph, i.e. that topology and dynamic operations are known to the algorithm. There exist use-cases however, where this assumption cannot be made. In vehicular ad-hoc networks, for example, a vehicle is only able to recognize the topology of the graph within wireless network transmission range. In this paper, we propose a combined uniform and heuristic search algorithm, which maintains shortest paths in highly dynamic graphs under the premise that graph operations are not globally known.

Keywords

Short Path Edge Weight Road Segment Short Path Problem Global Knowledge 
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.
    Dijkstra, E.W.: A note on two problems in connection with graphs. Numerische Mathematik 1, 269–271 (1959)MathSciNetzbMATHCrossRefGoogle Scholar
  2. 2.
    Nannicini, G., Liberti, L.: Shortest paths on dynamic graphs (2008)Google Scholar
  3. 3.
    Koenig, S., Likhachev, M., Furcy, D.: Lifelong planning A*. Artif. Intell. 155, 93–146 (2004)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Misra, S., Oommen, B.J.: Stochastic Learning Automata-Based Dynamic Algorithms for the Single Source Shortest Path Problem. In: Orchard, B., Yang, C., Ali, M. (eds.) IEA/AIE 2004. LNCS (LNAI), vol. 3029, pp. 239–248. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Cicerone, S., Stefano, G.D., Frigioni, D., Nanni, U.: A fully dynamic algorithm for distributed shortest paths. Theoretical Computer Science 297, 1–3 (2003)CrossRefGoogle Scholar
  6. 6.
    Demetrescu, C., Italiano, G.F.: A new approach to dynamic all pairs shortest paths. In: Proceedings of the Thirty-fifth Annual ACM Symposium on Theory of Computing, STOC 2003, pp. 159–166. ACM, New York (2003)CrossRefGoogle Scholar
  7. 7.
    Frigioni, D., Spaccamela, A.M., Nanni, U.: Fully dynamic algorithms for maintaining shortest path trees. Algorithms 34, 251–281 (2000)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Seet, B.-C., Liu, G., Lee, B.-S., Foh, C.-H., Wong, K.-J., Lee, K.-K.: A-STAR: A Mobile Ad Hoc Routing Strategy for Metropolis Vehicular Communications. In: Mitrou, N.M., Kontovasilis, K., Rouskas, G.N., Iliadis, I., Merakos, L. (eds.) NETWORKING 2004. LNCS, vol. 3042, pp. 989–999. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Granelli, F., Boato, G., Kliazovich, D., Vernazza, G.: Enhanced gpsr routing in multi-hop vehicular communications through movement awareness. IEEE Communications Letters 11, 781–783 (2007)CrossRefGoogle Scholar
  10. 10.
    Naumann, N., Schiinemann, B., Radusch, I.: Vsimrti - simulation runtime infrastructure for v2x communication scenarios. In: Proceedings of the 16th World Congress and Exhibition on Intelligent Transport Systems and Services (2009)Google Scholar
  11. 11.
    Barr, R., Haas, Z.J., van Renesse, R.: Jist: An efficient approach to simulation using virtual machines. Software Practice & Experience 35, 539–576 (2005)CrossRefGoogle Scholar
  12. 12.
    Krajzewicz, D., Hertkorn, G., Rössel, C., Wagner, P.: Sumo (simulation of urban mobility); an open-source traffic simulation. In: Proceedings of the 4th Middle East Symposium on Simulation and Modelling (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sandro Castronovo
    • 1
  • Björn Kunz
    • 1
  • Christian Müller
    • 1
    • 2
  1. 1.German Research Center for Artificial Intelligence (DFKI)SaarbrückenGermany
  2. 2.Action Line Intelligent Transportation SystemsEIT ICT LabsGermany

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