Chameleon: Latency and Resolution Aware Task Offloading for Visual-Based Assisted Driving
Chameleon: Latency and Resolution Aware Task Offloading for Visual-Based Assisted Driving
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DOI：
10.1109/tvt.2019.2924911
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发表时间：
2019-07
影响因子：
6.8
通讯作者：
Chao Zhu;Yi-Han Chiang;Abbas Mehrabi;Yu Xiao;Antti Ylä-Jääski;Yusheng Ji
中科院分区：
文献类型：
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作者：
Chao Zhu;Yi-Han Chiang;Abbas Mehrabi;Yu Xiao;Antti Ylä-Jääski;Yusheng Ji
新兴的基于视觉的驾驶辅助系统涉及时间关键型和数据密集型的计算任务，例如实时对象识别和场景理解。由于空间和电力容量的限制，在所有车辆上安装额外的计算设备是不可行的。为了解决这个问题，已经提出了不同的车辆雾计算场景，其中车辆生成的计算任务可以发送到位于例如5G蜂窝塔或移动公交车上的雾节点并在其上进行处理。在本文中，我们提出了变色龙，一种新的解决方案，任务卸载基于视觉的辅助驾驶。Chameleon考虑到服务需求和供应的时空变化，并提供基于部分可观察马尔可夫决策过程（POMDP）的延迟和分辨率感知的任务卸载策略。为了评估变色龙的有效性，我们模拟了车辆雾节点在一天中的不同时间的基础上收集的巴士轨迹在赫尔辛基的可用性，并使用真实世界的性能测量的视觉数据传输和处理。与自适应和随机任务卸载策略相比，Chameleon提供的基于POMDP的卸载策略将任务卸载的平均服务延迟缩短了65%，同时将处理图像的平均分辨率水平提高了83%。
Emerging visual-based driving assistance systems involve time-critical and data-intensive computational tasks, such as real-time object recognition and scene understanding. Due to the constraints on space and power capacity, it is not feasible to install extra computing devices on all the vehicles. To solve this problem, different scenarios of vehicular fog computing have been proposed, where computational tasks generated by vehicles can be sent to and processed at fog nodes located for example at 5G cell towers or moving buses. In this paper, we propose Chameleon, a novel solution for task offloading for visual-based assisted driving. Chameleon takes into account the spatiotemporal variation in service demand and supply, and provides latency and resolution aware task offloading strategies based on partially observable Markov decision process (POMDP). To evaluate the effectiveness of Chameleon, we simulate the availability of vehicular fog nodes at different times of day based on the bus trajectories collected in Helsinki, and use the real-world performance measurements of visual data transmission and processing. Compared with adaptive and random task offloading strategies, the POMDP-based offloading strategies provided by Chameleon shortens the average service latency of task offloading by up to 65% while increasing the average resolution level of processed images by up to 83%.