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Probability routing strategy for scale-free networks


  • Zhang, Xiaojun
  • He, Zishu
  • He, Zheng
  • Rayman-Bacchus, Lez


This study proposes a probability routing strategy for improving traffic capability on scale-free networks. Compared with the shortest path routing strategy depending on central nodes largely and the efficient routing strategy avoiding hub routers as much as possible, the probability routing strategy makes use of hub routers more efficiently, transferring approximate average amount of packs of the whole network. Simulation results indicate that the probability routing strategy has the highest network capacity among the three routing strategies. This strategy provides network capacity that can be more than 30 times higher than that of the shortest path routing strategy and over 50% higher than that of the efficient routing strategy. In addition, the average routing path length of our proposed strategy is over 10% shorter than that of the efficient routing strategy and only about 10% longer than that of the shortest path routing strategy.

Suggested Citation

  • Zhang, Xiaojun & He, Zishu & He, Zheng & Rayman-Bacchus, Lez, 2013. "Probability routing strategy for scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 953-958.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:4:p:953-958
    DOI: 10.1016/j.physa.2012.10.012

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    Cited by:

    1. Paul, Jomon Aliyas & MacDonald, Leo, 2016. "Location and capacity allocations decisions to mitigate the impacts of unexpected disasters," European Journal of Operational Research, Elsevier, vol. 251(1), pages 252-263.
    2. Paul, Jomon Aliyas & MacDonald, Leo, 2016. "Optimal location, capacity and timing of stockpiles for improved hurricane preparedness," International Journal of Production Economics, Elsevier, vol. 174(C), pages 11-28.


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