Mobile edge computing (MEC) is a new computing paradigm for addressing users’ ever-increasing demand for quality of service (QoS) in vehicular ad hoc networks (VANETs). The local delay is a performance metric that has a big impact on the QoS provisioned to users. This paper studies the analysis of the local delay in an MEC-based VANET based on stochastic geometry. An analytical model is first derived to analyze the average uplink local delay of a vehicle on a highway for sending a packet to an edge node along the highway. In deriving the model, the spatial distributions of vehicles and edge nodes are modeled as an independent one-dimensional (1-D) homogeneous Poisson point process (PPP). The edge node for accommodating the service request of a vehicle node is determined based on a nearest-receiver model. Moreover, a carrier sense multiple access (CSMA) mechanism is considered for channel access in the derived local delay model. The derived analytical model is validated through simulation results and the impacts of major parameters on the average uplink local delay are investigated. The derived model can be used to provide a basis for parameter settings in the deployment of edge nodes.

中文翻译：

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基于 MEC 的 VANET 上行链路本地延迟的建模与分析

移动边缘计算 (MEC) 是一种新的计算范式，用于解决用户对车载自组织网络 (VANET) 中不断增长的服务质量 (QoS) 需求。本地延迟是一个性能指标，对提供给用户的 QoS 有很大影响。本文研究了基于随机几何的基于 MEC 的 VANET 的局部延迟分析。首先导出分析模型来分析高速公路上车辆的平均上行链路本地延迟，以便将数据包发送到高速公路沿线的边缘节点。在推导模型时，车辆和边缘节点的空间分布被建模为独立的一维 (1-D) 齐次泊松点过程 (PPP)。基于最近接收器模型确定用于容纳车辆节点的服务请求的边缘节点。而且，在派生的本地延迟模型中，为信道访问考虑了载波侦听多路访问 (CSMA) 机制。通过仿真结果验证了导出的分析模型，并研究了主要参数对平均上行链路本地延迟的影响。派生模型可用于为边缘节点部署中的参数设置提供依据。