CSR:Small: Enabling Sensor-Rich Vehicular Applications with Edge Computing

CSR：Small：通过边缘计算实现传感器丰富的车辆应用

• 批准号: 1717064
• 负责人: Brian Noble
• 金额: $ 49.94万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1717064&HistoricalAwards=false
• 关键词: CSR; Small; Enabling; Sensor; Rich

This project is developing methodologies and systems that support sensor-rich vehicular applications by offloading computation to edge compute resources located at roadside and embedded within cellular networks. The modern vehicle has cameras, microphones, location and positioning sensors that all supplement detailed monitoring of vehicle motion and operation. These sensors can supply data for advanced applications, such as personal driving assistants, automated road hazard detection, and augmented display of driving data (e.g., highlighting turn-by-turn directions or available parking on the vehicle windshield). However, sensor-rich applications also require substantial computing power that is unavailable in the vehicle. These applications cannot leverage cloud resources because the latency of communicating with remote data centers is too high and the bandwidth available over wide-area networks is too limited. Instead, this project is supporting sensor-rich applications by offloading their computation to nearby servers located at the network edge. This work has the potential to enable applications with great societal benefit. Sensor-rich vehicular applications promise to improve driving efficiency; for example, by reducing congestion and idling time by guiding drivers directly to available parking spots. These applications can also substantially improve road safety; for example, by providing automated, crowd-sourced road hazard detection. The project is prototyping these applications and developing the infrastructure required for their deployment. The research results, traces of vehicular applications and environments, and open-source software artifacts developed by this project are available at: http://pervasive.eecs.umich.edu/vehicular-edge.html.Since vehicles will remain near edge resources for only limited periods of time, the project is creating methods for fast handover of state and computation from one edge resource to another. Vehicle mobility introduces considerable variability in network and service performance, so the project is investigating how the principled use of redundancy can improve average and worst-case response time. Finally, to support applications with extremely tight time bounds, the project is using speculative execution to hypothesize multiple possible futures that depend on vehicle speed and direction, calculate results based on those futures, and then select the appropriate response based upon actual vehicle motion during the time when calculations were made.

该项目正在开发方法和系统，通过将计算卸载到位于路边的Edge计算资源并嵌入蜂窝网络中的边缘资源来支持富含传感器的车辆应用。 现代车辆具有摄像头，麦克风，位置和定位传感器，这些传感器都补充了对车辆运动和操作的详细监视。 这些传感器可以为高级应用程序提供数据，例如个人驾驶助理，自动道路危险检测以及增强驾驶数据显示（例如，突出显示逐个转弯路线或车辆挡风玻璃上的可用停车位）。 但是，传感器丰富的应用程序还需要车辆不可用的实质性计算能力。 这些应用程序无法利用云资源，因为与远程数据中心进行通信的延迟太高，并且在广阔区域网络上可用的带宽过于限制。 取而代之的是，该项目通过将其计算卸载到位于网络边缘的附近服务器中来支持富含传感器的应用程序。这项工作有可能使社会利益巨大的申请。富含传感器的车辆应用有望提高驾驶效率；例如，通过将驾驶员直接引导到可用的停车位来减少交通拥堵和空转时间。 这些应用也可以大大提高道路安全；例如，通过提供自动化的，众包的道路危险检测。 该项目是原型的这些应用程序，并开发了其部署所需的基础架构。 The research results, traces of vehicular applications and environments, and open-source software artifacts developed by this project are available at: http://pervasive.eecs.umich.edu/vehicular-edge.html.Since vehicles will remain near edge resources for only limited periods of time, the project is creating methods for fast handover of state and computation from one edge resource to another.车辆移动性引入了网络和服务性能的很大差异，因此该项目正在研究冗余的原则使用如何改善平均值和最差的响应时间。 最后，为了支持极度紧密的时间范围的应用程序，该项目正在使用投机执行来假设取决于车辆速度和方向的多个可能的未来，请根据这些期货来计算结果，然后根据计算时间的实际车辆运动选择适当的响应。

项目成果

RAVEN: Improving Interactive Latency for the Connected Car

• DOI: 10.1145/3241539.3241571
• 发表时间: 2018-10
• 期刊: Proceedings of the 24th Annual International Conference on Mobile Computing and Networking
• 作者: Hyunjong Lee;J. Flinn;Basavaraj Tonshal

Gremlin: scheduling interactions in vehicular computing

Gremlin：车辆计算中的交互调度

• DOI: 10.1145/3132211.3134450
• 发表时间: 2017
• 期刊: ACM/IEEE Symposium on Edge Computing
• 作者: Lee, Kyungmin;Flinn, Jason;Noble, Brian D.
• 通讯作者: Noble, Brian D.