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MEC-based Stable Topology Prediction for Vehicular Networks

Use Case Details:

Attributes	Description	Informational
Type	New	The use case is proposed under the ICN BP family
Industry sector	Area: SDN & NFV University: Gachon University Country: Republic of Korea	We focus on the problems related to networking and software technology for a better connection. The technology that allows to build IT infrastructure, and aims to grow into a ‘Software Defined Infrastructure’ company.
Business driver	The 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 (1^st server) Edge node 1 (2^nd 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:

Attributes	Description	Informational
Type	Integrated Cloud Native NFV/App stack (ICN)
Blueprint Family	Existing
Use case	Stable network topology in IoV
Blueprint proposed name	MEC-based Stable Topology Prediction for Vehicular Networks
Initial POD cost	Satellite POD
Scale & Type	System will be developed/deployed in VMs.
Applications	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
SDN	ONOS will be used at the application layer
Workload type	VMs and Containers
Additional	4 Virtual Machines One Orchestration node 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

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Self Nominate for PTL (Y/N)

MalikAsif

Gachon University

malikasifmahmoodawan@gmail.com

Asia/Seoul (UTC+9)

Y

First (1^st)	Second (2^nd)
from: 29 Sep 2020 to: 31 Aug 2022	from: 20 Nov 2023 to: Present

Faisal Mehmood

Gachon University

Asia/Seoul (UTC+9)

from: 20 Nov 2023

to: Present

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