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Traffic dynamics in scale-free networks with tunable strength of community structure

Author

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  • Zhou, Ming-yang
  • Cai, Shi-min
  • Fu, Zhong-qian

Abstract

In this paper we systematically investigate the impact of community structure on traffic dynamics in scale-free networks based on local routing strategy. A growth model is introduced to construct scale-free networks with tunable strength of community structure, and a packet routing strategy with a parameter α is used to deal with the navigation and transportation of packets simultaneously. Simulations show that the maximal network capacity stands at α=−1 in the case of identical vertex capacity and monotonously decreases with the strength of community structure which suggests that the networks with fuzzy community structure (i.e., community strength is weak) are more efficient in delivering packets than those with pronounced community structure. To explain these results, the distribution of packets of each vertex is carefully studied. Our results indicate that the moderate strength of community structure is more convenient for the information transfer of real complex systems.

Suggested Citation

  • Zhou, Ming-yang & Cai, Shi-min & Fu, Zhong-qian, 2012. "Traffic dynamics in scale-free networks with tunable strength of community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1887-1893.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:4:p:1887-1893
    DOI: 10.1016/j.physa.2011.10.028
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    Cited by:

    1. Wang, Yi-Jia & Kuo, Yong-Hong & Huang, George Q. & Gu, Weihua & Hu, Yaohua, 2022. "Dynamic demand-driven bike station clustering," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).

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