Offloading Model and Algorithm for VANET Broadcast Applications

Vehicular Ad Hoc Network (VANET) is an important component of the Internet of Vehicles (IoV), providing a wide range of traffic safety, efficiency, and infotainment applications. These applications pose challenges to onboard computation and energy resources. To address these issues, Vehicle Edge Computing (VEC) has been introduced as a novel computing paradigm. Given the rapid and frequent changes in the topology of VANET networks due to the highspeed movement of vehicles, most VANET applications adopt broadcast communication, except for a few employing unicast communication. However, traditional task offloading models struggle to support broadcast applications. Therefore, this paper proposes a VANET broadcast task model to offload tasks from On-Board Units (OBUs) to Road-Side Units (RSUs) for the first time. To meet the requirement of low latency, an efficient polynomial-time heuristic algorithm is further proposed. Numerical results demonstrate the outstanding performance of the algorithm, with all instances being solved in less than 6ms, which significantly surpasses the performance of existing solvers. Moreover, the solutions obtained from the algorithm exhibit gaps below 1%, indicating their high acceptability and applicability in practical VANET applications. Furthermore, extensive numerical experiments provide valuable insights into the practical implementation of task offloading, suggesting an appropriate ratio of 6 between the number of OBUs and RSUs.

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Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-03-14
DOI
https://doi.org/10.1109/tits.2025.3548417
Citations
2
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
1.46

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article

Offloading Model and Algorithm for VANET Broadcast Applications

Hui Li, Chong Wang, Yongquan Chen
2 citations
IEEE Transactions on Intelligent Transportation Systems
Vehicular Ad Hoc Networks (VANETs)
1.46
article

Offloading Model and Algorithm for VANET Broadcast Applications

Hui Li, Chong Wang, Yongquan Chen
article en
2 citations

Abstract

Vehicular Ad Hoc Network (VANET) is an important component of the Internet of Vehicles (IoV), providing a wide range of traffic safety, efficiency, and infotainment applications. These applications pose challenges to onboard computation and energy resources. To address these issues, Vehicle Edge Computing (VEC) has been introduced as a novel computing paradigm. Given the rapid and frequent changes in the topology of VANET networks due to the highspeed movement of vehicles, most VANET applications adopt broadcast communication, except for a few employing unicast communication. However, traditional task offloading models struggle to support broadcast applications. Therefore, this paper proposes a VANET broadcast task model to offload tasks from On-Board Units (OBUs) to Road-Side Units (RSUs) for the first time. To meet the requirement of low latency, an efficient polynomial-time heuristic algorithm is further proposed. Numerical results demonstrate the outstanding performance of the algorithm, with all instances being solved in less than 6ms, which significantly surpasses the performance of existing solvers. Moreover, the solutions obtained from the algorithm exhibit gaps below 1%, indicating their high acceptability and applicability in practical VANET applications. Furthermore, extensive numerical experiments provide valuable insights into the practical implementation of task offloading, suggesting an appropriate ratio of 6 between the number of OBUs and RSUs.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(5)
Tsinghua–Berkeley Shenzhen Institute (CN), Chinese University of Hong Kong, Shenzhen (CN), Tsinghua University (CN)
Shenzhen Science and Technology Innovation Program, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 19%
Vehicular Ad Hoc Networks (VANETs)
1.46
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Offloading Model and Algorithm for VANET Broadcast Applications — Hui Li, Chong Wang, et al. · IEEE Transactions on Intelligent Transportation Systems (2025) | TGRS Research Map | TGRS