Peer-to-Peer Optimization in Large Unreliable Networks with Branch-and-Bound and Particle Swarms

  • Balázs Bánhelyi
  • Marco Biazzini
  • Alberto Montresor
  • Márk Jelasity
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5484)


Decentralized peer-to-peer (P2P) networks (lacking a GRID-style resource management and scheduling infrastructure) are an increasingly important computing platform. So far, little is known about the scaling and reliability of optimization algorithms in P2P environments. In this paper we present empirical results comparing two P2P algorithms for real-valued search spaces in large-scale and unreliable networks. Some interesting, and perhaps counter-intuitive findings are presented: for example, failures in the network can in fact significantly improve performance under some conditions. The two algorithms that are compared are a known distributed particle swarm optimization (PSO) algorithm and a novel P2P branch-and-bound (B&B) algorithm based on interval arithmetic. Although our B&B algorithm is not a black-box heuristic, the PSO algorithm is competitive in certain cases, in particular, in larger networks. Comparing two rather different paradigms for solving the same problem gives a better characterization of the limits and possibilities of optimization in P2P networks.


Network Size Shared Memory Interval Arithmetic Shared Memory Multiprocessor Unreliable Network 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kermarrec, A.M., van Steen, M. (eds.): ACM SIGOPS Operating Systems Review 41 (October 2007); Special issue on Gossip-Based NetworkingGoogle Scholar
  2. 2.
    Biazzini, M., Montresor, A., Brunato, M.: Towards a decentralized architecture for optimization. In: Proc. of IEEE IPDPS, Miami, FL, USA (April 2008)Google Scholar
  3. 3.
    Wickramasinghe, W.R.M.U.K., van Steen, M., Eiben, A.E.: Peer-to-peer evolutionary algorithms with adaptive autonomous selection. In: Proc. of GECCO, pp. 1460–1467. ACM Press, New York (2007)Google Scholar
  4. 4.
    Laredo, J.L.J., Eiben, E.A., van Steen, M., Castillo, P.A., Mora, A.M., Merelo, J.J.: P2P evolutionary algorithms: A suitable approach for tackling large instances in hard optimization problems. In: Luque, E., Margalef, T., Benítez, D. (eds.) Euro-Par 2008. LNCS, vol. 5168, pp. 622–631. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Jelasity, M., Montresor, A., Babaoglu, O.: A modular paradigm for building self-organizing peer-to-peer applications. In: Di Marzo Serugendo, G., Karageorgos, A., Rana, O.F., Zambonelli, F. (eds.) ESOA 2003. LNCS (LNAI), vol. 2977, pp. 265–282. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Bendjoudi, A., Melab, N., Talbi, E.G.: A parallel P2P branch-and-bound algorithm for computational grids. In: Proc. of IEEE CCGRID, Rio de Janeiro, Brazil, pp. 749–754 (2007)Google Scholar
  7. 7.
    Jelasity, M., Voulgaris, S., Guerraoui, R., Kermarrec, A.M., van Steen, M.: Gossip-based peer sampling. ACM Transactions on Computer Systems 25(3), 8 (2007)CrossRefGoogle Scholar
  8. 8.
    Talbi, E.G. (ed.): Parallel Combinatorial Optimization. Wiley, Chichester (2006)Google Scholar
  9. 9.
    Casado, L.G., Martinez, J.A., Garcia, I., Hendrix, E.M.T.: Branch-and-bound interval global optimization on shared memory multiprocessors. Optimization Methods and Software 23(5), 689–701 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Ratschek, H., Rokne, J.: Interval methods. In: Horst, R., Pardalos, P.M. (eds.) Handbook of Global Optimization. Kluwer, Dordrecht (1995)Google Scholar
  11. 11.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Balázs Bánhelyi
    • 1
  • Marco Biazzini
    • 2
  • Alberto Montresor
    • 2
  • Márk Jelasity
    • 3
  1. 1.University of SzegedHungary
  2. 2.University of TrentoItaly
  3. 3.University of Szeged and HASHungary

Personalised recommendations