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Content-aware rate allocation for efficient video streaming via dynamic network utility maximization

机译:通过动态网络实用程序最大化实现内容感知速率分配,实现高效的视频流

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摘要

Nowadays it is vital to design robust mechanisms to provide QoS for multimedia applications as an integral part of the network traffic. The main goal of this paper is to provide an efficient rate control scheme to support content-aware video transmission mechanism with buffer underflow avoidance at the receiver in congested networks. Towards this, we introduce a content-aware time-varying utility function, in which the quality impact of video content is incorporated into its mathematical expression. Moreover, we analytically model the buffer requirements of video sources in two ways: first as constraints of the optimization problem to guarantee a minimum rate demand for each source, and second as a penalty function embedded as part of the objective function attempting to achieve the highest possible rate for each source. Then, using the proposed analytical model, we formulate a dynamic network utility maximization problem, which aims to maximize the aggregate hybrid objective function of sources subject to capacity and buffer constraints. Finally, using primal-dual method, we solve DNUM problem and propose a distributed algorithm called CA-DNUM that optimally allocates the shared bandwidth to video streams. The experimental results demonstrate the efficacy and performance improvement of the proposed content-aware rate allocation algorithm for video sources in different scenarios.
机译:如今,设计健壮的机制以为多媒体应用程序提供QoS作为网络流量的组成部分至关重要。本文的主要目的是提供一种有效的速率控制方案,以支持在拥塞网络中的接收器处避免缓冲区下溢的内容感知视频传输机制。为此,我们引入了内容感知时变效用函数,其中将视频内容的质量影响合并到其数学表达式中。此外,我们通过两种方式对视频源的缓冲区需求进行分析建模:第一,作为优化问题的约束条件,以保证每个视频源的最低速率需求;第二,作为惩罚函数,嵌入到作为目标函数的一部分中,以实现最高的目标每个来源的可能费率。然后,使用提出的分析模型,我们制定了一个动态网络效用最大化问题,旨在最大化受容量和缓冲区约束的源的集合混合目标函数。最后,使用原始对偶方法,我们解决了DNUM问题,并提出了一种称为CA-DNUM的分布式算法,该算法可以将共享带宽最佳地分配给视频流。实验结果证明了针对不同场景下视频源的内容感知速率分配算法的有效性和性能改进。

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