H.264 Video Encoding-based Edge-assisted Mobile AR Systems: Network and Energy Issues
H.264 Video Encoding-based Edge-assisted Mobile AR Systems: Network and Energy Issues
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DOI：
10.1109/icc45855.2022.9838862
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Anik Mallik;Jiang Xie
中科院分区：
文献类型：
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作者：
Anik Mallik;Jiang Xie
边缘辅助的移动的增强现实（Edge-MAR）系统由于能够卸载繁重的计算负担而成为支持移动的设备的计算密集型和延迟敏感型应用的有效方式。然而，这种系统的网络和能量资源利用率很高。像H.264这样的视频编码方案可以帮助Edge-MAR系统降低延迟和带宽利用率，但代价是增加能耗。在本文中，我们提出了一个全面的研究，边缘MAR使用H.264视频编码的网络条件，资源利用率，检测精度，以及各种移动的设备的能耗为重点。我们通过测试平台的实验测量了目标检测流水线的每一段的延迟、能量、传输数据大小和准确性数据，并分析了Edge-MAR的非线性行为。接下来，我们展示了与测试系统的实验相关的挑战以及克服这些挑战的方法。最后，我们提出了基于回归的模型来分析计算不同的Edge-MAR参数，以达到预期的结果。这项广泛的研究为基于网络和能量感知的H.264视频编码的Edge-MAR系统设计提供了必要的指导。
Edge-assisted mobile augmented reality (Edge-MAR) systems have emerged as effective ways to support computation-intensive and latency-sensitive applications for mobile devices due to the offloading capability of heavy computational burdens. However, the network- and energy-resource utilization of such systems is high. Video encoding schemes like H.264 can help Edge-MAR systems reduce latency and bandwidth utilization but at the cost of increased energy consumption. In this paper, we present a comprehensive study of Edge-MAR using H.264 video encoding with a focus on network condition, resource utilization, detection accuracy, and energy consumption of various mobile devices. We collect latency, energy, transmitted data size, and accuracy data for each segment of an object detection pipeline measured through experiments with testbeds, and analyze the non-linear behaviors of Edge-MAR. Following this, we demonstrate the challenges associated with the experiments conducted to test the system as well as the ways to overcome them. Finally, we propose regression-based models to analytically compute different Edge-MAR parameters to achieve desired outcomes. This extensive study provides essential guidelines to network- and energy-aware H.264 video encoding-based Edge-MAR system design.