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QoE-based node selection strategy for edge computing enabled Internet-of-Vehicles (EC-IoV)

机译:用于边缘计算的车载互联网(EC-IoV)的基于QoE的节点选择策略

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With the emergence of computation intensive applications, a huge number of end-user devices are in urgent need of computational capabilities. Up-to-now, conventional cloud-based solutions are challenged by the bottleneck of network bandwidth, high delay and low quality of experience (QoE). In this paper, we illustrate the concept of edge computing enabled Internet-of-Vehicles (EC-IoV), which leverages connected vehicles as the edge computing platform. Then, we design a QoE based node selection (QNS) strategy, through which users can choose a proper edge node from quantities of vehicles to achieve a satisfying QoE on the whole. Simulation results demonstrate the QoE enhancement of QNS when compared with baseline strategies.
机译:随着计算密集型应用程序的出现,大量最终用户设备迫切需要计算功能。到目前为止,传统的基于云的解决方案面临着网络带宽,高延迟和低体验质量(QoE)的瓶颈的挑战。在本文中,我们说明了启用边缘计算的车载互联网(EC-IoV)的概念,该技术利用互联车辆作为边缘计算平台。然后,我们设计了一种基于QoE的节点选择(QNS)策略,通过该策略,用户可以从车辆数量中选择合适的边缘节点,从而总体上获得令人满意的QoE。仿真结果表明,与基线策略相比,QNS的QoE增强。

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