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Exploring activity-driven network with biased walks

Author

Listed:
  • Yan Wang

    (College of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, P. R. China)

  • Ding Juan Wu

    (School of Health Management, Guangzhou Medical University, Guangzhou 510006, P. R. China)

  • Fang Lv

    (Department of Mathematics, Luoyang Normal University, Luoyang 471934, P. R. China)

  • Meng Long Su

    (Department of Mathematics, Luoyang Normal University, Luoyang 471934, P. R. China)

Abstract

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Suggested Citation

  • Yan Wang & Ding Juan Wu & Fang Lv & Meng Long Su, 2017. "Exploring activity-driven network with biased walks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(09), pages 1-10, September.
  • Handle: RePEc:wsi:ijmpcx:v:28:y:2017:i:09:n:s012918311750111x
    DOI: 10.1142/S012918311750111X
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