IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v15y2019i3p1550147719837859.html
   My bibliography  Save this article

Joint communication and computing resource allocation in vehicular edge computing

Author

Listed:
  • Jianan Sun
  • Qing Gu
  • Tao Zheng
  • Ping Dong
  • Yajuan Qin

Abstract

The emergence of computation-intensive vehicle applications poses a significant challenge to the limited computation capacity of on-board equipments. Mobile edge computing has been recognized as a promising paradigm to provide high-performance vehicle services by offloading the applications to edge servers. However, it is still a challenge to efficiently utilize the available resources of vehicle nodes. In this article, we introduce mobile edge computing technology to vehicular ad hoc network to build a vehicular edge computing system, which provides a wide range of reliable services by utilizing the computing resources of vehicles on the road. Then, we study the computation offloading decision problem in this system and propose a novel multi-objective vehicular edge computing task scheduling algorithm which jointly optimizes the allocation of communication and computing resources. Extensive performance evaluation demonstrates that the proposed algorithm can effectively shorten the task execution time and has high reliability.

Suggested Citation

  • Jianan Sun & Qing Gu & Tao Zheng & Ping Dong & Yajuan Qin, 2019. "Joint communication and computing resource allocation in vehicular edge computing," International Journal of Distributed Sensor Networks, , vol. 15(3), pages 15501477198, March.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:3:p:1550147719837859
    DOI: 10.1177/1550147719837859
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147719837859
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147719837859?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
    ---><---

    References listed on IDEAS

    as
    1. N. Cherfi & M. Hifi, 2010. "A column generation method for the multiple-choice multi-dimensional knapsack problem," Computational Optimization and Applications, Springer, vol. 46(1), pages 51-73, May.
    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. Hui Li & Lishuang Pei & Dan Liao & Ming Zhang & Du Xu & Xiong Wang, 2020. "Achieving privacy protection for crowdsourcing application in edge-assistant vehicular networking," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 75(1), pages 1-14, September.

    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. Jaeyoung Yang & Yong-Hyuk Kim & Yourim Yoon, 2022. "A Memetic Algorithm with a Novel Repair Heuristic for the Multiple-Choice Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 10(4), pages 1-15, February.
    2. Ewa M. Bednarczuk & Janusz Miroforidis & Przemysław Pyzel, 2018. "A multi-criteria approach to approximate solution of multiple-choice knapsack problem," Computational Optimization and Applications, Springer, vol. 70(3), pages 889-910, July.
    3. Caserta, Marco & Voß, Stefan, 2019. "The robust multiple-choice multidimensional knapsack problem," Omega, Elsevier, vol. 86(C), pages 16-27.
    4. Renata Mansini & Roberto Zanotti, 2020. "A Core-Based Exact Algorithm for the Multidimensional Multiple Choice Knapsack Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1061-1079, October.
    5. Gao, Chao & Lu, Guanzhou & Yao, Xin & Li, Jinlong, 2017. "An iterative pseudo-gap enumeration approach for the Multidimensional Multiple-choice Knapsack Problem," European Journal of Operational Research, Elsevier, vol. 260(1), pages 1-11.
    6. Lamanna, Leonardo & Mansini, Renata & Zanotti, Roberto, 2022. "A two-phase kernel search variant for the multidimensional multiple-choice knapsack problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 53-65.

    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:sae:intdis:v:15:y:2019:i:3:p:1550147719837859. 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: SAGE Publications (email available below). General contact details of provider: .

    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.