Research on Vehicle Resource Allocation Strategy Assisted by Idle Resources in Complex Urban Channel Environments

Traditional vehicle networking resource allocation strategies are difficult to meet diverse high-quality communication needs in high dynamic vehicle scenarios, especially in congested areas such as intersections, which suffer from low scheduling efficiency, network congestion, and high latency. In r...

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Bibliographic Details
Published in2024 7th International Conference on Computer Information Science and Application Technology (CISAT) pp. 1398 - 1402
Main Authors Hu, Yaowen, Dong, Aofei
Format Conference Proceeding
LanguageEnglish
Published IEEE 12.07.2024
Subjects
Approximation algorithms
component
Dynamic scheduling
Heuristic algorithms
Optimization
Resource allocation
Resource management
Roads
Simulation
Spectrum sharing
Transforms
Urban areas
Vehicle communication
Vehicle dynamics
Vehicle networking
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Summary:Traditional vehicle networking resource allocation strategies are difficult to meet diverse high-quality communication needs in high dynamic vehicle scenarios, especially in congested areas such as intersections, which suffer from low scheduling efficiency, network congestion, and high latency. In response to these challenges, this article proposes a vehicle resource allocation strategy based on idle resources assistance. This strategy targets the highly dynamic and frequently changing channel environment in urban environments, utilizing idle roadside resources to assist vehicle communication in optimizing resource allocation and improving network performance. This article constructs a resource allocation algorithm for this strategy. Firstly, the vehicle communication capability maximization algorithm utilizes the Bernstein approximation method to transform constraint conditions into computable forms, and combines binary optimization to achieve the maximization of vehicle communication capability. Simulation experiments show that resource allocation strategies and algorithms significantly improve the total channel capacity in the vehicular network. Compared with existing resource allocation algorithms, it has obvious advantages and has been proven to have good performance.
DOI:10.1109/CISAT62382.2024.10695187