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Data Acquisition Based on Stable Matching of Bipartite Graph in Cooperative Vehicle–Infrastructure Systems

机译:车载基础设施系统中基于二部图稳定匹配的数据采集

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摘要

Existing studies on data acquisition in vehicular networks often take the mobile vehicular nodes as data carriers. However, their autonomous movements, limited resources and security risks impact the quality of services. In this article, we propose a data acquisition model using stable matching of bipartite graph in cooperative vehicle-infrastructure systems, namely, DAS. Contents are distributed to roadside units, while vehicular nodes support supplementary storage. The original distribution problem is formulated as a stable matching problem of bipartite graph, where the data and the storage cells compose two sides of vertices. Regarding the factors relevant with the access ratio and delay, the preference rankings for contents and roadside units are calculated, respectively. With a multi-replica preprocessing algorithm to handle the potential one-to-many mapping, the matching problem is addressed in polynomial time. In addition, vehicular nodes carry and forward assistant contents to deliver the failed packets because of bandwidth competition. Furthermore, an incentive strategy is put forward to boost the vehicle cooperation and to achieve a fair bandwidth allocation at roadside units. Experiments show that DAS achieves a high access ratio and a small storage cost with an acceptable delay.
机译:关于车辆网络中的数据采集的现有研究经常将移动车辆节点作为数据载体。但是,它们的自主移动,有限的资源和安全风险会影响服务质量。在本文中,我们提出了一种在合作车辆基础设施系统DAS中使用二部图的稳定匹配的数据采集模型。内容被分发到路边单元,而车辆节点则支持补充存储。原始分布问题被公式化为二部图的稳定匹配问题,其中数据和存储单元构成了顶点的两侧。关于与访问率和延迟有关的因素,分别计算内容和路边单元的偏好等级。利用多副本预处理算法来处理潜在的一对多映射,可以在多项式时间内解决匹配问题。另外,由于带宽竞争,车辆节点携带并转发辅助内容以传送失败的分组。此外,提出了一种激励策略,以促进车辆合作并在路边单位实现公平的带宽分配。实验表明,DAS具有较高的访问率和较小的存储成本,并且具有可接受的延迟。

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