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CoDA: Connectivity-Oriented Data Dissemination Algorithm for Vehicular Internet Access Networks

机译:CoDA:车载互联网访问网络的面向连接的数据分发算法

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As a typical scenario of mobile Internet, a vehicular Internet access network is a network where vehicles exploit wireless technologies to communicate with infrastructure directly or indirectly via other vehicles or road-side units in high speed. Thus, opportunistic interactions through neighboring vehicles and infrastructure networks can be utilized to exchange useful data and information. Much effort has been made to improve the total amount of data delivered under the delay tolerant network model, in which data links from and to vehicles are always intermittent. However, the network connectivity is critical to real time or interactive applications and services. In this paper, we investigate the problem to maximize network connectivity in vehicular Internet access networks, where vehicles adopt both vehicle-to-vehicle and vehicle-to-infrastructure communications. First, we analyze the characteristics of network connectivity in vehicular Internet access networks and derive a closed-form expression to represent the connectivity probability under specific RSU deployment model and vehicle arrival rate. Then, we develop a connectivity-oriented data dissemination (CoDA) algorithm to maximize the network connectivity probability in vehicular Internet access networks based on probabilistic analysis, which considers multiple factors related to the network connectivity. Finally, we validate the CoDA algorithm through extensive simulations based on the traces from real practise.
机译:作为移动互联网的典型场景,车载互联网接入网络是车辆利用无线技术直接或间接地经由其他车辆或路侧单元与基础设施进行通信的网络。因此,可以利用通过邻近车辆和基础设施网络的机会互动来交换有用的数据和信息。为了改善在延迟容忍网络模型下传送的数据总量,已经做出了很多努力,在这种模型中,来往车辆的数据链路始终是断断续续的。但是,网络连接对于实时或交互式应用程序和服务至关重要。在本文中,我们研究了在车辆采用车辆对车辆和车辆对基础设施通信的情况下,如何在车辆Internet接入网络中最大化网络连接性的问题。首先,我们分析了车辆互联网访问网络中网络连接的特征,并得出一个封闭形式的表达式来表示特定RSU部署模型和车辆到达率下的连接概率。然后,我们基于概率分析,考虑了与网络连接性相关的多个因素,开发了一种面向连接性的数据分发(CoDA)算法,以最大化车辆互联网访问网络中的网络连接性概率。最后,我们根据实际经验中的痕迹,通过广泛的仿真对CoDA算法进行了验证。

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