High-Reliability Low-Latency Intelligent Geographic Routing Protocol for Vehicle Road Cooperation System

The vehicle road cooperation system is designed to enable intelligent and collaborative communication between vehicles and vehicles, infrastructure, and pedestrians to reduce road accidents and improve road efficiency. As a critical component of this, vehicle-to-vehicle (V2V) communication is expected to achieve efficient information interaction between vehicles and support services, such as collision warning and operation assistance. However, due to the high mobility of vehicles and channel fading, V2V communication suffers from link instability, high latency, and low-resource utilization. To address these issues, this article proposes a high-reliability low-latency intelligent geographic routing (HRLLIGR) protocol based on the greedy perimeter stateless routing (GPSR) protocol to improve its performance in such highly dynamic networks. The main mechanisms of HRLLIGR include a reliable greedy forwarding algorithm based on the evaluation of link stability metrics, a low-latency area prediction forwarding algorithm for routing voids, and an intelligent routing update mechanism to reduce routing overhead. Simulation results suggest that the HRLLIGR protocol outperforms traditional routing protocols, such as ad-hoc on-demand distance vector (AODV), optimized link state routing (OLSR), and GPSR regarding reliability, latency, and overhead. Specifically, compared to the GPSR protocol, it achieves 13.7% improvement in packet delivery rate, 21.3% reduction in average end-to-end latency, and 15.1% decrease in routing overhead.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-09-23
DOI
https://doi.org/10.1109/jiot.2024.3465519
Citations
2
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
0.66

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article

High-Reliability Low-Latency Intelligent Geographic Routing Protocol for Vehicle Road Cooperation System

Osama Alfarraj, Alireza Jolfaei, Xin Jian, Shaokun Liu et al.
2 citations
IEEE Internet of Things Journal
Robotics and Automated Systems
0.66
article

High-Reliability Low-Latency Intelligent Geographic Routing Protocol for Vehicle Road Cooperation System

Osama Alfarraj, Alireza Jolfaei, Xin Jian, Shaokun Liu, Keping Yu, Zhu Xiao-gang, Lingyi Xie, Yangjie Li
article en
2 citations

Abstract

The vehicle road cooperation system is designed to enable intelligent and collaborative communication between vehicles and vehicles, infrastructure, and pedestrians to reduce road accidents and improve road efficiency. As a critical component of this, vehicle-to-vehicle (V2V) communication is expected to achieve efficient information interaction between vehicles and support services, such as collision warning and operation assistance. However, due to the high mobility of vehicles and channel fading, V2V communication suffers from link instability, high latency, and low-resource utilization. To address these issues, this article proposes a high-reliability low-latency intelligent geographic routing (HRLLIGR) protocol based on the greedy perimeter stateless routing (GPSR) protocol to improve its performance in such highly dynamic networks. The main mechanisms of HRLLIGR include a reliable greedy forwarding algorithm based on the evaluation of link stability metrics, a low-latency area prediction forwarding algorithm for routing voids, and an intelligent routing update mechanism to reduce routing overhead. Simulation results suggest that the HRLLIGR protocol outperforms traditional routing protocols, such as ad-hoc on-demand distance vector (AODV), optimized link state routing (OLSR), and GPSR regarding reliability, latency, and overhead. Specifically, compared to the GPSR protocol, it achieves 13.7% improvement in packet delivery rate, 21.3% reduction in average end-to-end latency, and 15.1% decrease in routing overhead.

IEEE Internet of Things JournalVol. 12(2)
Nanchang University (CN), Chongqing University (CN), Flinders University (AU), Hosei University (JP), King Saud University (SA)
National Natural Science Foundation of China, Key Research and Development Program of Jiangxi Province, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 30%
Robotics and Automated Systems
0.66
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