Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design

In recent years, with the rapid development of the Internet of Vehicles (IoV) and the widespread application of integrated sensing and communication (ISAC) in the IoV, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latency-sensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this article studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to the RSU and the vehicle platoon via nonorthogonal multiple access (NOMA) technology, and construct a multiobjective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among the ISAC vehicle, the RSU, and the vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-03-31
DOI
https://doi.org/10.1109/jiot.2025.3553677
Citations
2
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
4.96
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article

Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design

Minghui Dai, Lina Wang, Haijun Zhang, Weihong Wu
2 citations
IEEE Internet of Things Journal
Privacy-Preserving Technologies in Data
4.96
article

Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design

Minghui Dai, Lina Wang, Haijun Zhang, Weihong Wu
article en
2 citations

Abstract

In recent years, with the rapid development of the Internet of Vehicles (IoV) and the widespread application of integrated sensing and communication (ISAC) in the IoV, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latency-sensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this article studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to the RSU and the vehicle platoon via nonorthogonal multiple access (NOMA) technology, and construct a multiobjective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among the ISAC vehicle, the RSU, and the vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy.

IEEE Internet of Things JournalVol. 12(13)
Donghua University (CN), University of Science and Technology Beijing (CN)
Affordable and clean energy
Openalex Percentile: Top 6%
Privacy-Preserving Technologies in Data
4.96
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