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首页> 外文期刊>Journal of network and systems management >Joint In-network Video Rate Adaptation and Measurement-Based Admission Control: Algorithm Design and Evaluation
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Joint In-network Video Rate Adaptation and Measurement-Based Admission Control: Algorithm Design and Evaluation

机译:联合网络内视频速率自适应和基于测量的准入控制:算法设计和评估

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摘要

The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the quality of experience (QoE). Both admission control and scalable video coding techniques can control the QoE by blocking connections or adapting the video rate but influence each other's performance. In this article, we propose an in-network video rate adaptation mechanism that enables a provider to define a policy on how the video rate adaptation should be performed to maximize the provider's objective (e.g., a maximization of revenue or QoE). We discuss the need for a close interaction of the video rate adaptation algorithm with a measurement based admission control system, allowing to effectively orchestrate both algorithms and timely switch from video rate adaptation to the blocking of connections. We propose two different rate adaptation decision algorithms that calculate which videos need to be adapted: an optimal one in terms of the provider's policy and a heuristic based on the utility of each connection. Through an extensive performance evaluation, we show the impact of both algorithms on the rate adaptation, network utilisation and the stability of the video rate adaptation. We show that both algorithms outperform other configurations with at least 10 %. Moreover, we show that the proposed heuristic is about 500 times faster than the optimal algorithm and experiences only a performance drop of approximately 2 %, given the investigated video delivery scenario.
机译:多媒体服务为网络和服务提供商提供的重要的新收入机会也带来了重要的管理挑战。对于提供商来说,控制用户提供和感知的视频质量(通常称为体验质量(QoE))非常重要。准入控制和可伸缩视频编码技术都可以通过阻止连接或调整视频速率来控制QoE,但会影响彼此的性能。在本文中,我们提出了一种网络内视频速率适配机制,该机制使提供商可以定义有关如何执行视频速率适配以最大化提供商目标(例如,收益或QoE最大化)的策略。我们讨论了视频速率自适应算法与基于测量的准入控制系统之间紧密交互的需求,允许有效地编排这两种算法并及时从视频速率自适应切换到连接阻塞。我们提出了两种不同的速率自适应决策算法,这些算法可以计算出需要对哪些视频进行自适应处理:根据提供商的政策,一种最佳视频;以及一种基于每个连接的效用的启发式算法。通过广泛的性能评估,我们显示了这两种算法对速率适配,网络利用率和视频速率适配的稳定性的影响。我们证明这两种算法的性能至少比其他配置高出10%。此外,我们表明,在调查的视频交付场景下,拟议的启发式算法比最佳算法快约500倍,并且性能只会下降约2%。

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