Load Balancing in Dynamic Networks by Bounded Delays Asynchronous Diffusion

  • Jacques M. Bahi
  • Sylvain Contassot-Vivier
  • Arnaud Giersch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6449)


Load balancing is a well known problem, which has been extensively addressed in parallel algorithmic. However, there subsist some contexts in which the existing algorithms cannot be used. One of these contexts is the case of dynamic networks where the links between the different elements are intermittent. We propose in this paper an efficient algorithm, based on asynchronous diffusion, to perform load balancing in such a context. A convergence theorem is proposed and proved. Finally, experimental results performed in the SimGrid environment confirm the efficiency of our algorithm.


Load balancing dynamic network asynchronism 


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  1. 1.
    Bertsekas, D., Tsitsiklis, J.: Parallel and Distributed Computation. Prentice Hall, Englewood Cliffs (1999)zbMATHGoogle Scholar
  2. 2.
    Casanova, H., Legrand, A., Quinson, M.: SimGrid: a Generic Framework for Large-Scale Distributed Experiments. In: 10th IEEE International Conference on Computer Modeling and Simulation (March 2008)Google Scholar
  3. 3.
    Cortes, A., Ripoll, A., Cedo, F., Senar, M.A., Luque, E.: An asynchronous and iterative load balancing algorithm for discrete load model. Journal of Parallel and Distributed Computing 62(12), 1729–1746 (2002)CrossRefzbMATHGoogle Scholar
  4. 4.
    Cybenko, G.: Dynamic load balancing for distributed memory processors. Journal of Parallel and Distributed Computing 7, 279–301 (1989)CrossRefGoogle Scholar
  5. 5.
    Elsässer, R., Monien, B., Preis, R.: Diffusion schemes for load balancing on heterogeneous networks. Theory of Computing Systems 35, 305–320 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Fatès, N.: Directed percolation phenomena in asynchronous elementary cellular automata. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds.) ACRI 2006. LNCS, vol. 4173, pp. 667–675. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Genaud, S., Giersch, A., Vivien, F.: Load-balancing scatter operations for grid computing. Parallel Computing 30(8), 923–946 (2004)CrossRefGoogle Scholar
  8. 8.
    Bahi, J.M., Couturier, R., Vernier, F.: Synchronous distributed load balancing on dynamic networks. Journal of Parallel and Dist. Comp. 65(11), 1397–1405 (2005)CrossRefzbMATHGoogle Scholar
  9. 9.
    Kumar, V.: Introduction to Parallel Computing. Addison-Wesley Longman Publishing Co., Inc., Boston (2002)Google Scholar
  10. 10.
    Miguet, S., Robert, Y.: Elastic load-balancing for image processing algorithms. In: Zima, H.P. (ed.) ACPC 1991. LNCS, vol. 591, pp. 438–451. Springer, Heidelberg (1992)CrossRefGoogle Scholar
  11. 11.
    Willebeek-Lemair, M.H.: Startegies for dynamic load balancing on highly parallel computers. IEEE Trans. on Parallel and Distributed Systems 4(9), 979–993 (1993)CrossRefGoogle Scholar
  12. 12.
    Li, Y., Lan, Z.: A survey of load balancing in grid computing. In: Zhang, J., He, J.-H., Fu, Y. (eds.) CIS 2004. LNCS, vol. 3314, pp. 280–285. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jacques M. Bahi
    • 1
  • Sylvain Contassot-Vivier
    • 2
    • 3
  • Arnaud Giersch
    • 1
  1. 1.LIFCUniversity of Franche-ComtéBelfortFrance
  2. 2.LORIAUniversity Henri PoincaréNancyFrance
  3. 3.AlGorille INRIA TeamFrance

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