Sustain Vehicle-Crowds via Traffic Signal Adjustments
Sustain Vehicle-Crowds via Traffic Signal Adjustments
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DOI：
10.1109/vtcfall.2018.8690577
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发表时间：
2018-08
期刊：
影响因子：
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通讯作者：
Meng Kuai;P. Subedi;X. Hong;A. Hainen
中科院分区：
文献类型：
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作者：
Meng Kuai;P. Subedi;X. Hong;A. Hainen
基于车辆人群（V-crowd）的云预计将支持高需求的移动边缘计算应用程序。然而，v-crowd 托管 cloudlet 应用程序的能力很大程度上受到其自身可持续性的影响。在可能有助于能力和维持 v 人群的因素中，交通信号协调起着重要作用。在本文中，我们通过实证方法研究它们之间的相互依赖关系。我们将定义新的指标来量化影响，并使用数据驱动的模拟通过操纵信号偏移作为交通信号协调的控制旋钮来获得结果。目标是使用度量结果来制定指南，为特定级别的 v-crowd 属性提供更佳的偏移选择，从而实现 Cloudlet 应用程序的更好性能。
Vehicle-crowd (V-crowd) based cloudlets are envisioned to support high-demand mobile edge computing applications. Yet, a v-crowd's capability to host cloudlet applications is significantly affected by the sustainability of itself. Among the factors that may contribute to the capability and sustaining the v-crowd, traffic signal coordination plays an important role. In this paper, we study the interdependence between them through an empirical approach. We'll define new metrics to quantify the impact, and use data driven simulation to obtain results by manipulating signals offset as a control knob of traffic signal coordination. The goal is to use the results in terms of the metrics to develop guidelines that offer choices of offsets preferable for certain levels of v-crowd properties so as to achieve better performance of cloudlet applications.