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Fog Node Optimum Placement and Configuration Technique for VANETs

机译:雾节点最佳放置和藤条配置技术

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Intelligent Transportation Systems (ITS) are nowadays considered very important applications of smart cities. One of the most important technologies that are utilized to support ITS is Vehicular Ad-hoc Networks (VANETs). In VANETs, vehicles communicate with each other (V2V) or with the infrastructure (Roadside Units) (V2I). Roadside Units (RSUs) collect data from vehicles in the coverage area and send it to cloud servers through the Internet. Cloud servers have high performance computational and storage capabilities that ITS applications require for data processing. However, due to the real-time requirements of the ITS applications, cloud approach alone cannot be guaranteed to satisfy the strict time constraints due to long latency access of the centralized cloud server. Fog Computing is an emerging approach that extends the services of cloud computing to the edge of the network. Fog Computing can be utilized in VANETs through deployment of fog nodes into RSUs. One of the major challenges is identifying the optimum number, locations and computational capabilities of the RSUs particularly in urban regions where obstacles exist heavily inside the coverage area of the RSUs. In this paper, we consider the optimization problem of fog-based RSU placement where the objective is to maximize the achieved level of service quality in a cost-effective way. The problem is formulated as a Satisfiability Modulo Theories (SMT) problem and solved using Microsoft Z3. The proposed approach is able to generate a set of solutions as Pareto front. We obtained data from OpenStreetMap for Cairo city. Our approach outperforms other solutions in the literature in terms of cost.
机译:如今,智能交通系统(其)被认为是智能城市的非常重要的应用。用于支持其的最重要的技术之一是车辆ad-hoc网络(VANET)。在VANET中,车辆彼此通信(V2V)或基础设施(路边单位)(V2I)。路边单位(RSUS)从覆盖范围内的车辆中收集数据,并通过互联网将其发送到云服务器。云服务器具有高性能计算和存储功能,其应用程序需要进行数据处理。但是,由于其应用的实时要求,由于集中式云服务器的长期访问,因此不能保证单独的云方法以满足严格的时间约束。雾计算是一种新兴的方法,将云计算的服务扩展到网络边缘。通过将雾节点部署到RSU,可以在VANET中使用雾计算。其中一个主要挑战是识别RSUS的最佳数量,位置和计算能力,特别是在城市地区,其中障碍物在RSU的覆盖面积内部存在大幅上。在本文中,我们考虑了基于FOG的RSU放置的优化问题,其中目标是以成本效益的方式最大限度地实现达到的服务质量水平。该问题被制定为可满足的模数理论(SMT)问题,并使用Microsoft Z3解决。所提出的方法能够生成一组解决方案作为帕累托前面。我们从OpenStreetMap获得了开罗城的数据。我们的方法在成本方面以文献中的其他解决方案胜过了其他解决方案。

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