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Internet Provisioning in VANETs: Performance Modeling of Drive-Thru Scenarios

机译:Vanets中的互联网配置:驱动器通过场景的性能建模

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Drive-thru-Internet is a scenario in cooperative intelligent transportation systems (C-ITSs), where a road-side unit (RSU) provides multimedia services to vehicles that pass by. Performance of the drive-thru-Internet depends on various factors, including data traffic intensity, vehicle traffic density, and radio-link quality within the coverage area of the RSU, and must be evaluated at the stage of system design in order to fulfill the quality-of-service requirements of the customers in C-ITS. In this paper, we present an analytical framework that models downlink traffic in a drive-thru-Internet scenario by means of a multidimensional Markov process: the packet arrivals in the RSU buffer constitute Poisson processes and the transmission times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we use iterative perturbation techniques to calculate the stationary distribution of the Markov chain. Our numerical results reveal that the proposed approach yields accurate estimates of various performance metrics, such as the mean queue content and the mean packet delay for a wide range of workloads.
机译:Drive-Thru-Internet是合作智能运输系统(C-ITS)的场景,其中路边单元(RSU)为通过的车辆提供多媒体服务。驱动器通过互联网的性能取决于各种因素,包括RSU的覆盖区域内的数据流量强度,车辆流量密度和无线电链路质量,并且必须在系统设计的阶段进行评估,以实现C-ITS中客户的服务质量要求。在本文中,我们介绍了一种分析框架,通过多维马尔可夫进程:RSU缓冲器中的数据包到达,构成泊松过程,传输时间是指数分布的分组到达。考虑到与多维马尔可夫流程相关的状态空间爆炸问题,我们使用迭代扰动技术来计算马尔可夫链的静止分布。我们的数值结果表明,所提出的方法产生准确的各种性能指标的估计,例如平均工作量的平均队列内容和平均数据包延迟。

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