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Expolynomial Modelling for Supporting VANET Infrastructure Planning

机译:支持VANET基础架构规划的指数模型

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The deployment of Intelligent Transportation Systems (ITS) is a challenge for industry and scientific community. Traffic characteristics change widely within a single day, therefore, ITS engineers and researchers must deal with that dynamic behavior. On the other hand, once the ITS depends on networking services, specific studies are required to consider the communication parameters along with vehicle mobility. In this paper, we propose an analytical model based on the Stochastic Petri Net (SPN) theory for evaluating Vehicular Ad-Hoc Networks (VANETs) infrastructures, considering mobility and network parameters, and the respective constraints. We employ expolynomial distributions to represent Roadside Unit (RSU) service rates. Those probability distributions allow the approximation of many analytical and empirical data. Results show that parameters such as vehicular density, message frequency, and RSU radius may affect significantly the overall system performance.
机译:智能交通系统(ITS)的部署对工业界和科学界都是一个挑战。流量特性在一天之内发生很大变化,因此,ITS工程师和研究人员必须应对这种动态行为。另一方面,一旦ITS依赖于网络服务,就需要进行专门的研究来考虑通信参数以及车辆的机动性。在本文中,我们提出了一种基于随机Petri网(SPN)理论的分析模型,用于评估车辆自组织网络(VANET)基础结构,同时考虑了移动性和网络参数以及各自的约束。我们采用多项式分布来表示路边单位(RSU)的服务费率。这些概率分布可以近似许多分析和经验数据。结果表明,诸如车辆密度,消息频率和RSU半径之类的参数可能会显着影响整个系统的性能。

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