End-to-end versus explicit feedback measurement in 802.11 networks

M. Kazantzidis, M. Gerla
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引用次数: 45

Abstract

Higher layer protocols in wireless networks need to dynamically adapt to observed network response. The common approach is that each session employs end-to-end monitoring to estimate quantities of interest, like delay, delay jitter and available bandwidth. A less conventional approach is to employ lower layer explicit feedback mechanisms in place or in aid of end-to-end efforts. Available bandwidth measurements are known to follow multi-modal distributions and therefore are especially difficult to measure and filter, even in wired networks. In 802.11-based multi-hop networks obtaining usable end-to-end measurements is questionable. They are affected by a combination of a large number of transient variables due to the virtual carrier sense, head of line problems on each link and mobility. Motivated by this, we are developing a network explicit feedback mechanism. Our study of this accurate network feedback architecture aids in the cost/benefit analysis of an important trade-off: deployment of network support mechanisms for transports and QoS, versus the simple, scalable and easily deployable end-to-end solution. We test our solution in: (i) multimedia adaptation and (ii) measurement based call admission. Loss rates of end-to-end adaptive video and audio connections have been more than 4 times higher than in the network feedback case. A simple call admission strategy has also proved very effective using the feedback. In our experiments it led the network to a maximal performance and stable operating point.
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802.11网络中的端到端与显式反馈测量
无线网络中的高层协议需要动态适应观察到的网络响应。常见的方法是,每个会话使用端到端监控来估计感兴趣的数量,如延迟、延迟抖动和可用带宽。一种不太传统的方法是采用较低层次的显式反馈机制,或者辅助端到端工作。已知可用带宽测量遵循多模态分布,因此尤其难以测量和过滤,即使在有线网络中也是如此。在基于802.11的多跳网络中,获得可用的端到端测量是有问题的。它们受到虚拟载波感知、各链路上的线头问题和机动性等大量瞬态变量的综合影响。在此激励下,我们正在开发一种网络显式反馈机制。我们对这种准确的网络反馈架构的研究有助于对一个重要的权衡进行成本/收益分析:部署传输和QoS的网络支持机制,与简单、可扩展和易于部署的端到端解决方案。我们测试了我们的解决方案:(i)多媒体适应和(ii)基于测量的呼叫接纳。端到端自适应视频和音频连接的损失率比网络反馈情况高出4倍以上。一个简单的呼叫接纳策略也被证明是非常有效的使用反馈。在我们的实验中,它使网络达到了最大的性能和稳定的工作点。
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