ARVE：车辆到边缘网中的增强现实应用
本文为SIGCOMM 2018 Workshop (Mobile Edge Communications, MECOMM)论文。
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本文作者包含4位，Pengyuan Zhou@University of Helsinki, Finland；Wenxiao Zhang@Hong Kong University of Science and Technology, Hong Kong; Tristan Braud@Hong Kong University of Science and Technology, Hong Kong; Pan Hui@Hong Kong University of Science and Technology, Hong Kong； Jussi Kangasharju@University of Helsinki, Finland
ABSTRACT (摘要）
Vehicular communication applications, be it for driver-assisting augmented reality systems or fully driverless vehicles, require an efficient communication infrastructure for timely information delivery. Centralized, cloud-based infrastructures present latencies too high to satisfy the requirements of emergency information processing and transmission. In this paper, we present a novel Vehicle-to-Edge (ARVE) infrastructure, with computational units co-located with the base stations and aggregation points. Embedding computation at the edge of the network allows to reduce the overall latency compared to vehicle-to-cloud and signifcantly trim the complexity of vehicle-to-vehicle communication. To demonstrate the efficiency of our solution, we apply these principles on an augmented reality head-up display. In this use case, vehicular communication is exploited to connect vehicle’s vision, and quickly propagate emergency information. ARVE is a general system framework, applicable to many practical scenarios. Our preliminary evaluation shows that ARVE noticeably decreases transmission latency with reasonable capital expenditure.
无论是驾驶辅助增强现实系统还是完全无人驾驶车辆，车辆通信应用都需要有效的通信基础设施来及时传递信息。集中式、基于云的基础设施存在过高的延迟，无法满足紧急信息处理和传输的要求。在本文中，我们提出了一种新颖的车辆到边缘（ARVE）基础设施，其计算单元与基站和聚合点共存。与车辆到云相比，在网络边缘嵌入计算允许减少总体延迟并且显着地减少车辆到车辆通信的复杂性。为了展示我们解决方案的效率，我们将这些原则应用于增强现实汽车平视显示器。在该用例中，利用车辆通信来连接车辆的视觉，并快速传播紧急信息。 ARVE是一个通用的系统框架，适用于许多实际场景。我们的初步评估表明，ARVE通过合理的资本支出显着降低了传输延迟。