Architecture for Resource Allocation in the Internet of Vehicles for Cooperating Driving System

Internet of Vehicles (IoV) is a complex system that consists of resource types such as vehicles, humans, and sensors. Although the Internet of Vehicles is complex, it improvises communication among vehicles on the roads. Quality of service (QoS) enabled the cooperative driving system (CDS) based on...

Full description

Saved in:
Bibliographic Details
Published in:Journal of advanced transportation Vol. 2021; pp. 1 - 11
Main Authors: kalsoom, Nafeesa, Ahmad, Iftikhar, Alroobaea, Roobaea, Raza, Muhammad Ahsan, Khalid, Samina, Ahmed, Zaheed, Ali, Ihsan
Format: Journal Article
Language:English
Published: London Hindawi 2021
John Wiley & Sons, Inc
Wiley
Subjects:
ISSN:0197-6729, 2042-3195
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Internet of Vehicles (IoV) is a complex system that consists of resource types such as vehicles, humans, and sensors. Although the Internet of Vehicles is complex, it improvises communication among vehicles on the roads. Quality of service (QoS) enabled the cooperative driving system (CDS) based on 5G technology, enabling vehicles to communicate and cooperate to improve road traffic efficiency. Due to the high vehicle density and limited resources (bandwidth) of current network infrastructure, sometimes a better channel that meets the requirements of cooperative driving is not available that causes network congestion, which directly influences the overall QoS of the CDS. To overcome this, we proposed a 5G network-based architecture for CDS that incorporates a D2D technology-based resource allocation scheme. The proposed network architecture and cooperative behavior-based scheme helps in improving QoS for CDS. We implemented our proposed scheme by incorporating the density-based scattered clustering algorithm with noise for vehicular clustering. The proposed scheme’s performance shows significant improvement in terms of throughput compared with existing D2D approaches.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0197-6729
2042-3195
DOI:10.1155/2021/6637568