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使用DeepStream和简单的实时服务器构建流服务应用程序,使用容器化用于边缘计算
Wen-Chung Shih1, Zheng-Yao Wang2, Endah Kristiani2,3
1Department of M-Commerce and Multimedia Applications, Asia University, Taichung City 413305, Taiwan.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
这项研究表明,NVIDIA Jetson Xavier NX上的容器化流媒体应用与物理机器相匹配. 对于边缘计算视频流,WebRTC提供较低的延迟,但硬件限制了多个连接.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 软件工程 软件工程 软件工程
背景情况:
- 边缘计算需要高效,可扩展的流媒体解决方案.
- 在边缘部署中,NVIDIA Jetson Xavier NX和Docker是关键技术.
- 评估用于实时视频处理的容器化应用程序至关重要.
研究的目的:
- 在边缘硬件上评估容器化流媒体应用程序的性能.
- 为了比较不同流媒体协议 (WebRTC,HLS,RTMP) 的延迟和资源利用情况.
- 识别基于边缘的流媒体架构中的性能瓶和硬件限制.
主要方法:
- 使用NVIDIA Jetson Xavier NX硬件和Docker进行应用部署.
- 评估了DeepStream和简单的实时服务器用于流媒体服务应用程序.
- 在WebRTC,HLS和RTMP协议中进行了性能和负载测试.
主要成果:
- 容器化应用实现了与物理机器相提并论的性能.
- 与HLS (10秒以上) 相比,WebRTC表现出优越的低延迟 (大约5s).
- 与HLS和RTMP相比,WebRTC的CPU使用率 (>40%) 较高;内存使用率稳定.
- 系统性能降低了与超过三个同时使用的设备.
结论:
- 容器化对于高性能边缘流应用程序是可行的.
- 尽管CPU负载较高,但WebRTC适用于低延迟边缘视频流.
- 在NVIDIA Jetson Xavier NX上的硬件限制限制了众多并发连接的可扩展性.
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