IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v494y2018icp129-139.html
   My bibliography  Save this article

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

Author

Listed:
  • Tan, Mian
  • Yang, Tinghong
  • Chen, Xing
  • Yang, Gang
  • Zhu, Guoqing
  • Holme, Petter
  • Zhao, Jing

Abstract

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming “communication shortcuts” between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes’ selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

Suggested Citation

  • Tan, Mian & Yang, Tinghong & Chen, Xing & Yang, Gang & Zhu, Guoqing & Holme, Petter & Zhao, Jing, 2018. "A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 129-139.
  • Handle: RePEc:eee:phsmap:v:494:y:2018:i:c:p:129-139
    DOI: 10.1016/j.physa.2017.12.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117312694
    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.2017.12.032?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. Eun Lee & Petter Holme, 2016. "Impact of mobility structure on optimization of small-world networks of mobile agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(6), pages 1-8, June.
    2. P. Holme & B. J. Kim & V. Fodor, 2010. "Heterogeneous attachment strategies optimize the topology of dynamic wireless networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(4), pages 597-604, February.
    3. Nicolas Langer & Andreas Pedroni & Lutz Jäncke, 2013. "The Problem of Thresholding in Small-World Network Analysis," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
    2. Wang, Shuliang & Sun, Jingya & Zhang, Jianhua & Dong, Qiqi & Gu, Xifeng & Chen, Chen, 2023. "Attack-Defense game analysis of critical infrastructure network based on Cournot model with fixed operating nodes," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    3. Sun, Chengbin & Luo, Chao, 2020. "Co-evolution of influence-based preferential selection and limited resource with multi-games on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 374(C).

    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. Katarzyna J Blinowska & Maciej Kaminski, 2013. "Functional Brain Networks: Random, “Small World” or Deterministic?," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.

    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:494:y:2018:i:c:p:129-139. 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.