深圳大学学报理工版

为解决异构网络因采用主动队列管理进行拥塞控制,无法区分视频流中不同结构和内容的数据包,难以提高视频播出质量的问题,提出一种结合视觉运动特性的可分级视频拥塞控制机制.该机制基于视觉运动特性的视频数据包重要性标记方法,根据当前队列长度及丢包率与队列长度的非线性关系,改进已有的自适应随机早期检测.当网络发生拥塞时,能根据网络状况和数据包的重要性调整丢包策略.以视频质量分析仪PQA600的注意力加权峰值信噪比、差异平均主观评分和注意加权差异平均主观评分作为评价指标.NS-2仿真实验结果表明,该方法能降低丢包率,提高网络吞吐量,改善视频播出质量.

In current heterogeneous network video transmissions, the active queue management cannot consider the effects of different structures and content packets on the quality of video broadcast. A new visual motion characteristics-based scalable video congestion control mechanism is proposed to solve this problem. This mechanism presents a vision motion characteristics-based video packet importance marking method and improves existing adaptive random early detection according to the current queue length and the nonlinear relationship between the packet loss rate and queue length. When congestion occurs, the packet loss policy is adjusted according to network conditions and the importance of video packets. Attention weighted peak signal to noise ratio(AW-PSNR), difference in mean opinion score(DMOS)and attention weighted difference in mean opinion score(ADMOS)of PQA600 are used as video quality assessment values. Results from NS-2 simulation platform have shown that the packet loss rate is reduced; both the network throughput and the video broadcast quality are improved in this mechanism.

引言
1 视频码流重要性分析与拥塞控制现有研究成果
2 结合视觉运动特性的可分级视频拥塞控制机制
3 仿真实验与结果分析
4 结语

图1 数据包重要性标记流程图<br/>Fig.1 Flowchart of packet importance tagging

图1 数据包重要性标记流程图
Fig.1 Flowchart of packet importance tagging

图2 基于队列长度的非线性ARED算法描述<br/>Fig.2 The description of QnLARED algorithm

图2 基于队列长度的非线性ARED算法描述
Fig.2 The description of QnLARED algorithm

图3 QnLARED算法丢弃概率与Qavg的关系<br/>Fig.3 The relationship between packet loss rate and Qavg of QnLARED

图3 QnLARED算法丢弃概率与Qavg的关系
Fig.3 The relationship between packet loss rate and Qavg of QnLARED

图4 网络仿真拓扑图<br/>Fig.4 Network simulation topology

图4 网络仿真拓扑图
Fig.4 Network simulation topology

表1 Foreman序列实验结果比较<br/>Table 1 Comparison of Foreman sequence

表1 Foreman序列实验结果比较
Table 1 Comparison of Foreman sequence

表2 News序列实验结果比较<br/>Table 2 Comparison of News sequence

表2 News序列实验结果比较
Table 2 Comparison of News sequence

表3 Mobile序列实验结果比较<br/>Table 3 Comparison of Mobile sequence

表3 Mobile序列实验结果比较
Table 3 Comparison of Mobile sequence

图5 3序列丢包率结果比较<br/>Fig.5 Packet loss rate comparison of Foreman sequence、News sequence and Mobile sequence

图5 3序列丢包率结果比较
Fig.5 Packet loss rate comparison of Foreman sequence、News sequence and Mobile sequence

图6 Mobile序列吞吐量比较图 <br/>Fig.6 Throughput comparison of Mobile sequence

图6 Mobile序列吞吐量比较图
Fig.6 Throughput comparison of Mobile sequence

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备注

引言

1 视频码流重要性分析与拥塞控制现有研究成果

2 结合视觉运动特性的可分级视频拥塞控制机制

3 仿真实验与结果分析

4 结语

期刊信息

备注

引言

1 视频码流重要性分析与拥塞控制现有研究成果

2 结合视觉运动特性的可分级视频拥塞控制机制

3 仿真实验与结果分析

4 结 语

期刊信息

4 结语