Network Multimedia QoS Class Recognition Based on Improved K-SVD
WANG Zaijian① DONG Yuning② TANG Pingping①② YANG Lingyun①② ZHANG Hui②
①(College of Physics and Electronic Information, Anhui Normal University, Wuhu 241000, China) ②(College of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China)
摘要 该文基于网络多媒体业务QoS(Quality of Service)特征特点，提出网络业务QoS类识别算法。探索了新的多媒体业务QoS类划分模式，在QoS分类的基础上，可以通过将具有相同或相似QoS需求特征的业务流聚集生成聚集流。聚集流划分使用较少的QoS特征，借助聚集流可以在合理的粒度上区分多媒体业务。该文从QoS特征出发分析了聚集流识别的特点，利用网络多媒体业务典型QoS特征的稀疏性，使用改进K-SVD(Kernel Singular Value Decomposition)进行字典学习，实现网络多媒体业务QoS类识别。实验结果表明，该文算法比现有方法具有更高的QoS类识别准确性。
Abstract：According to QoS characteristics of network multimedia service, this paper proposes a algorithm of network multimedia QoS class recognition. This paper studies new multimedia traffic QoS class division mode. According to new QoS classes defined, Flow Aggregation (FA) can be formed by gathering multimedia traffic flows with similar QoS characteristics. Network multimedia QoS class recognition prefers fewer QoS features by FA, and it is possible to divide network multimedia traffics in suitable granularity based on FA. This paper analyzes the property of FA recognition from QoS perspective, uses improved K-SVD (Kernel Singular Value Decomposition) to learn dictionary by using the sparse representation of typical QoS characteristics of network multimedia traffics, and presents a network multimedia QoS class recognition method. Experiment results show that the proposed recognition method can achieve more accurate QoS class recognition than previous methods.
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