AvCloak:一个用于视频会议应用中黑箱延迟测量的工具

Andrew Kryczka, A. Arefin, K. Nahrstedt
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引用次数: 17

摘要

随着视频会议(VC)所依赖的高带宽、低延迟网络的日益普及,可用视频会议(VC)应用程序的使用量和数量正在增加。由于VC应用程序支持实时人机交互,因此损害交互性的性能问题是社会问题。目前,由于VC应用程序的专有性质,性能测量不容易获得,然而,这种测量将是有用的,因为它们使研究人员能够轻松评估架构和设计决策对性能的影响,定量比较VC应用程序,并确定服务水平协议(SLA)遵从性。在本文中,我们介绍了一个名为Av Cloak的工具,它能够测量专有VC应用程序中的几个关键性能指标:嘴到耳朵的延迟和抖动,捕获到显示的延迟和抖动,以及视听同步偏差。AvCloak通过包裹(“隐形”)VC应用程序的音频/视频输入/输出并通过它们传输时间戳数据来实现这些测量。在发送端,AvCloak合成媒体数据编码时间戳,并将其提供给VC应用程序的媒体输入,而在接收端,AvCloak从VC应用程序的媒体输出中解码时间戳。由于AvCloak仅通过其媒体输入和输出与目标VC应用程序交互,因此它将目标应用程序视为黑盒,因此适用于任意VC应用程序。我们提供广泛的分析来测量AvCloak的开销,并展示如何使用两个流行的VC应用程序提高测量的准确性:Skype和b谷歌+ Hangouts。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AvCloak: A Tool for Black Box Latency Measurements in Video Conferencing Applications
The usage and number of available video conferencing (VC) applications are rising as the high-bandwidth, low latency networks on which they depend become increasingly prevalent. Since VC applications support real-time human interaction, problems with performance that impair interactivity are social issues. Currently, performance measurements cannot easily be obtained due to the proprietary nature of VC applications, however, such measurements would be useful because they enable researchers to easily evaluate the performance impact of architectural and design decisions, quantitatively compare VC applications, and determine service level agreement (SLA) compliance. In this paper, we present a tool called Av Cloak that is capable of measuring several key performance metrics in proprietary VC applications: mouth-to-ear latency and jitter, capture-to-display latency and jitter, and audio-visual synchronization skew. AvCloak takes these measurements by wrapping ("cloaking") the VC application's audio/video inputs/outputs and transmitting timestamp data through them. At the sender side, AvCloak synthesizes media data encoding timestamps and feeds them to the VC application's media inputs, while at the receiver side, AvCloak decodes timestamps from the VC application's media outputs. Since AvCloak interacts with the target VC application only through its media inputs and outputs, it treats the target application as a black box and is thus applicable to arbitrary VC applications. We provide extensive analyses to measure AvCloak's overhead and show how to improve accuracy in measurements using two popular VC applications: Skype and Google+ Hangouts.
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