IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i18p4699-4708.html
   My bibliography  Save this article

First passage time of multiple Brownian particles on networks with applications

Author

Listed:
  • Wang, Shao-Ping
  • Pei, Wen-Jiang

Abstract

In this article, we study some theoretical and technological problems with relation to multiple Brownian particles on networks. We are especially interested in the behavior of the first arriving Brownian particle when all the Brownian particles start out from the source s simultaneously and head to the destination h randomly. We analyze the first passage time (FPT) Ysh(z) and the mean first passage time (MFPT) 〈Ysh(z)〉 of multiple Brownian particles on complex networks. Equations of Ysh(z) and 〈Ysh(z)〉 are obtained. On a variety of commonly encountered networks, we observe first passage properties of multiple Brownian particles from different aspects. We find that 〈Ysh(z)〉 drops substantially when particle number z increases at the first stage, and converges to dsh, the distance between the source and the destination when z→∞. The distribution of FPT Prob{Ysh(z)=t},t=0,1,2,… is also analyzed in these networks. The distribution curve peaks up towards t=dsh when z increases. Consequently, if particle number z is set appropriately large, the first arriving Brownian particle will go along the shortest or near shortest paths between the source and the destination with high probability. Simulations confirm our analysis. Based on theoretical studies, we also investigate some practical problems using multiple Brownian particles, such as communication on P2P networks, optimal routing in small world networks, phenomenon of asymmetry in scale-free networks, information spreading in social networks, pervasion of viruses on the Internet, and so on. Our analytic and experimental results on multiple Brownian particles provide useful evidence for further understanding and properly tackling these problems.

Suggested Citation

  • Wang, Shao-Ping & Pei, Wen-Jiang, 2008. "First passage time of multiple Brownian particles on networks with applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4699-4708.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:18:p:4699-4708
    DOI: 10.1016/j.physa.2008.03.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108003373
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2008.03.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Petter Holme, 2003. "Congestion And Centrality In Traffic Flow On Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 163-176.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Zi-Yi & Han, Jing-Ti & Zhao, Jun, 2017. "Identifying node spreading influence for tunable clustering coefficient networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 242-250.
    2. Perez, Yuri & Pereira, Fabio Henrique, 2021. "Simulation of traffic light disruptions in street networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    3. Ghosh, Saptarshi & Banerjee, Avishek & Ganguly, Niloy, 2012. "Some insights on the recent spate of accidents in Indian Railways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2917-2929.
    4. Angelo Furno & Nour-Eddin El Faouzi & Rajesh Sharma & Eugenio Zimeo, 2021. "Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-35, March.
    5. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    6. Cirunay, Michelle T. & Batac, Rene C., 2023. "Evolution of the periphery of a self-organized road network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    7. Wen, Tzai-Hung & Chin, Wei-Chien-Benny & Lai, Pei-Chun, 2017. "Understanding the topological characteristics and flow complexity of urban traffic congestion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 166-177.
    8. Batac, Rene C. & Cirunay, Michelle T., 2022. "Shortest paths along urban road network peripheries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    9. Bilong Shen & Weimin Zheng & Kathleen M. Carley, 2018. "Urban Activity Mining Framework for Ride Sharing Systems Based on Vehicular Social Networks," Networks and Spatial Economics, Springer, vol. 18(3), pages 705-734, September.
    10. Tam, Wai M. & Lau, Francis C.M. & Tse, Chi K. & Xia, Yongxiang & Shan, Xiuming, 2006. "Effect of clustering in a complex user network on the telephone traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 745-753.
    11. Xiangyang Cao & Bingzhong Zhou & Qiang Tang & Jiaqi Li & Donghui Shi, 2018. "Urban Wasteful Transport and Its Estimation Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, December.
    12. Wang, Weiping & Yang, Saini & Hu, Fuyu & Stanley, H. Eugene & He, Shuai & Shi, Mimi, 2018. "An approach for cascading effects within critical infrastructure systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 164-177.
    13. Wang, Yuhong & Cullinane, Kevin, 2016. "Determinants of port centrality in maritime container transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 326-340.
    14. Rui Ding & Jian Yin & Peng Dai & Lu Jiao & Rong Li & Tongfei Li & Jianjun Wu, 2019. "Optimal Topology of Multilayer Urban Traffic Networks," Complexity, Hindawi, vol. 2019, pages 1-19, October.
    15. Ribas, Lucas C. & Bruno, Odemir M., 2020. "Dynamic texture analysis using networks generated by deterministic partially self-avoiding walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:387:y:2008:i:18:p:4699-4708. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.