自修复视频流架构在RTSP服务器上的应用

C. Cunha, L. Silva
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引用次数: 1

摘要

流媒体现在是互联网上的杀手级应用之一。流媒体服务的可用性是一个关键问题,因为消费者的期望是围绕着几十年的传统电视体验。服务器性能在流媒体中特别重要,因为它对延迟的敏感性使其容易受到性能异常的影响。当前的服务器级性能分析工作无法处理工作负载无法解释的性能故障。我们提出了一个流服务器的自修复架构,该架构由心脏的生物隐喻维持,通过检测心律失常(流内容的传输延迟)和会话探测来预测性能故障,探索主动服务器恢复。我们通过在几个资源耗尽场景下的实验工作来评估RTSP流中的方法。结果表明,对于大多数故障场景,我们的方法能够在故障发生前几秒钟预测和定位服务故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of a Self-Healing Video-Streaming Architecture to RTSP Servers
Streaming media is now one of the killer applications on the Internet. Availability in streaming services is a critical concern, as consumer expectations are drawn around decades of traditional TV experience. Server performance has particular importance in streaming, as its sensitiveness to delays makes it vulnerable to performance anomalies. Current work on server-level performance analysis fails to cope with performance failures not explained by the workload. We propose a self-healing architecture for streaming servers sustained by a biological metaphor of heart that explores proactive server recovery by anticipating performance failures through detection of arrhythmias (transmission delays of streaming content) and session probing. We evaluated the approach in RTSP streaming through experimental work in several resource exhaustion scenarios. Results have shown that our approach is able to predict and localize service failures several seconds before their occurrence for most failure scenarios.
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