IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v12y2020i10p172-d428524.html
   My bibliography  Save this article

An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers

Author

Listed:
  • Yanjun Shi

    (School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Yijia Guo

    (School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Lingling Lv

    (School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Keshuai Zhang

    (School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China)

Abstract

The fast development of connected vehicles with support for various V2X (vehicle-to-everything) applications carries high demand for quality of edge services, which concerns microservice deployment and edge computing. We herein propose an efficient resource scheduling strategy to containerize microservice deployment for better performance. Firstly, we quantify three crucial factors (resource utilization, resource utilization balancing, and microservice dependencies) in resource scheduling. Then, we propose a multi-objective model to achieve equilibrium in these factors and a multiple fitness genetic algorithm (MFGA) for the balance between resource utilization, resource utilization balancing, and calling distance, where a container dynamic migration strategy in the crossover and mutation process of the algorithm is provided. The simulated results from Container-CloudSim showed the effectiveness of our MFGA.

Suggested Citation

  • Yanjun Shi & Yijia Guo & Lingling Lv & Keshuai Zhang, 2020. "An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers," Future Internet, MDPI, vol. 12(10), pages 1-15, October.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:10:p:172-:d:428524
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/12/10/172/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/12/10/172/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Massimo Condoluci & Laurent Gallo & Laurent Mussot & Apostolos Kousaridas & Panagiotis Spapis & Maliheh Mahlouji & Toktam Mahmoodi, 2019. "5G V2X System-Level Architecture of 5GCAR Project," Future Internet, MDPI, vol. 11(10), pages 1-26, October.
    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. Antonella Molinaro & Claudia Campolo & Jérôme Härri & Christian Esteve Rothenberg & Alexey Vinel, 2020. "5G-V2X Communications and Networking for Connected and Autonomous Vehicles," Future Internet, MDPI, vol. 12(7), pages 1-3, July.

    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:gam:jftint:v:12:y:2020:i:10:p:172-:d:428524. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.