4.5 Article

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

Journal

JOURNAL OF ADVANCED TRANSPORTATION
Volume 2021, Issue -, Pages -

Publisher

WILEY-HINDAWI
DOI: 10.1155/2021/6637568

Keywords

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Funding

  1. Taif University Researchers Supporting Project, Taif University, Taif, Saudi Arabia [TURSP-2020/36]
  2. Faculty of Computer Science and Information Technology, University of Malaya [PG035-2016A]

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Internet of Vehicles (IoV) is a complex system consisting of vehicles, humans, and sensors, which improves communication among vehicles on the roads. Quality of service (QoS) enabled by the cooperative driving system (CDS) based on 5G technology enhances road traffic efficiency. To improve QoS for CDS, a 5G network-based architecture and D2D technology-based resource allocation scheme were proposed, along with a density-based scattered clustering algorithm for vehicular clustering. The proposed scheme shows significant improvement in throughput compared to existing D2D approaches.
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.

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