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Fine grained classification of Internet multimedia traffics

机译:互联网多媒体流量的细分类

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For the purposes of efficient network resource management and QoS (Quality of Service) support of different multimedia services, this paper proposes a fine grained classification scheme for Internet multimedia traffics using a novel low-complexity feature selection method based on coefficient of variation. We focus on web-browsing and network video services in this work. A number of QoS and network resource requirements related statistical features of these applications are studied and validated by their effectiveness in web-browsing and video traffic classification. This scheme classifies multimedia services with the combinations of these statistical features. Experiments are performed on a large scale real network multimedia traffic data. The results show that the proposed method can achieve better classification performance in contrast to existing methods.
机译:为了有效地支持不同多媒体服务的网络资源管理和QoS(服务质量),本文提出了一种新颖的基于变异系数的低复杂度特征选择方法,用于Internet多媒体流量的细粒度分类方案。在这项工作中,我们专注于网络浏览和网络视频服务。通过研究这些应用程序在Web浏览和视频流量分类中的有效性,研究并验证了许多与QoS和网络资源需求相关的统计功能。该方案利用这些统计特征的组合对多媒体服务进行分类。实验是在大规模的真实网络多媒体流量数据上进行的。结果表明,与现有方法相比,该方法具有更好的分类性能。

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