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rootMEC-based Stable Topology Prediction for Vehicular Networks

MEC-based Stable Topology Prediction for Vehicular Networks

Use Case Details:




TypeNewThe use case is proposed under the ICN BP family
Industry sector

Area: SDN & NFV
University: Gachon University
Country: Republic of Korea

ATTO RESEARCH focuses We focus on the problems related to networking and software technology for a better connection. It has created a The technology that allows to build IT infrastructure, and aims to grow into a ‘Software Defined Infrastructure’ company.
Business driverThe stable vehicular network is essential to enable various applications such as autonomous driving through VANETs. Proposed MEC architecture tends to enable a promising infrastructure where a stable network topology can be predicted locally to improve the network performance by providing intensive calculation for vehicles in the adjacent roads. Thus, converging the two concepts of MEC and topology prediction can provide a strong use case for the vehicular networks such as proactive path stabilization.The MEC-based Efficient Routing Algorithm can provide a stable path by using the predicted future position for the nearby vehicles. The information can also be made available to the adjacent road resulting from being useful to provide a stable topology on the road tracks.
Business use case
  • Edge cloud deployable at RSUs to support applications such as ML-based location prediction, topology stabilization

Business cost - Initial build

Minimal configuration is three servers in total:

  • Master/Database node (1st server)
  • Edge node 1 (2nd server)
  • Edge node 2 (3rd server)
Price factor depends on the cost of RSU quality, and should be only considered for physical deployment. i.e. wireless or wired.
Business cost - Operational

Virtual environment does not require cost.

Operational need

Using the frontend GUI to:

  • Orchestrate virtual resources
Manage the edge applications

Additional details
  • Support of path within a Single operator domain

PPT is attached as proposal statement.

Species Details:





Integrated Cloud Native NFV/App stack (ICN)

Blueprint Family


Use case

Stable network topology in IoV

Blueprint proposed nameMEC-based Stable Topology Prediction for Vehicular Networks

Initial POD cost

Satellite POD

Scale & Type

System will be developed/deployed in VMs.

  • ML model
  • LTE network services
  • ProSe Functions

Open Air Interface (OAI) provided LTE network services will be used.

Infrastructure orchestration

  • OpenStack latest/stable release – VM orchestration
  • Kubernetes-based container orchestration
  • WeaveNet -based Container Networking
  • VNF Orchestration – ONAP
  • OS – Ubuntu 18.X LTS
  • CICD - Jenkins 2.249.1 LTS


ONOS will be used at the application layer

Workload type

VMs and Containers


  • 4 Virtual Machines
    1. One Orchestration node
    2. Three Edge nodes
  • Jenkins for Continuous Integration and Continuous Delivery
  • Personal servers will be integrated with the Linux Foundation servers

Committers and PTL (Project Technical Lead)

Please enter in all names of the committers for the project.

PTL is done off of self nomination process.  If you wish to be considered for the PTL, please indicate that by putting a Y in the self nomination column (use the slide to move the table left to right).  Per Akraino rules, if there is only one nominee, that person becomes PTL (when confirmed by the Akraino TSC).  If there is more than nominee, we will then have an election.
The election process is open and will go through 7 Oct. 2020 at Noon Pacific time. 


Committer Company

 Committer Contact InfoTime Zone

Committer Bio

Committer Picture

Self Nominate for PTL (Y/N)

Gachon University

Asia/Seoul (UTC+9)

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First (1st)Second (2nd)




to: Present

Gachon University

Asia/Seoul (UTC+9)


to: Present

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