IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v15y2023i12p391-d1291840.html
   My bibliography  Save this article

A Comprehensive Survey Exploring the Multifaceted Interplay between Mobile Edge Computing and Vehicular Networks

Author

Listed:
  • Ali Pashazadeh

    (Department of Information Engineering, University of Florence, Via Santa Marta 3, 50139 Florence, Italy
    Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy)

  • Giovanni Nardini

    (Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy)

  • Giovanni Stea

    (Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy)

Abstract

In recent years, the need for computation-intensive applications in mobile networks requiring more storage, powerful processors, and real-time responses has risen substantially. Vehicular networks play an important role in this ecosystem, as they must support multiple services, such as traffic monitoring or sharing of data involving different aspects of the vehicular traffic. Moreover, new resource-hungry applications have been envisaged, such as autonomous driving or in-cruise entertainment, hence making the demand for computation and storage resources one of the most important challenges in vehicular networks. In this context, Mobile Edge Computing (MEC) has become the key technology to handle these problems by providing cloud-like capabilities at the edge of mobile networks to support delay-sensitive and computation-intensive tasks. In the meantime, researchers have envisaged use of onboard vehicle resources to extend the computing capabilities of MEC systems. This paper presents a comprehensive review of the most recent works related to MEC-assisted vehicular networks, as well as vehicle-assisted MEC systems. We illustrate the MEC system architecture and discuss its deployment in vehicular environments, as well as the key technologies to realize this integration. After that, we review the recent literature by identifying three different areas, i.e.: (i) MEC providing additional resources to vehicles (e.g., for task offloading); (ii) MEC enabling innovative vehicular applications (e.g., platooning), and (iii) vehicular networks providing additional resources to MEC systems. Finally, we discuss open challenges and future research directions, addressing the possible interplays between MEC systems and vehicular networks.

Suggested Citation

  • Ali Pashazadeh & Giovanni Nardini & Giovanni Stea, 2023. "A Comprehensive Survey Exploring the Multifaceted Interplay between Mobile Edge Computing and Vehicular Networks," Future Internet, MDPI, vol. 15(12), pages 1-45, November.
  • Handle: RePEc:gam:jftint:v:15:y:2023:i:12:p:391-:d:1291840
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/15/12/391/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/15/12/391/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vasilios Patsias & Petros Amanatidis & Dimitris Karampatzakis & Thomas Lagkas & Kalliopi Michalakopoulou & Alexandros Nikitas, 2023. "Task Allocation Methods and Optimization Techniques in Edge Computing: A Systematic Review of the Literature," Future Internet, MDPI, vol. 15(8), pages 1-30, July.
    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. Zuopeng Li & Hengshuai Ju & Zepeng Ren, 2023. "A Learning Game-Based Approach to Task-Dependent Edge Resource Allocation," Future Internet, MDPI, vol. 15(12), pages 1-21, December.
    2. Rafael Moreno-Vozmediano & Rubén S. Montero & Eduardo Huedo & Ignacio M. Llorente, 2024. "Intelligent Resource Orchestration for 5G Edge Infrastructures," Future Internet, MDPI, vol. 16(3), pages 1-31, March.

    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:15:y:2023:i:12:p:391-:d:1291840. 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.