关键词: 特征选择, 视频流分类, 多级分类器

Abstract: Accurate identification and categorization of multimedia traffic is the premise of end to end QoS （Quality of Service） guarantees. Today, the dramatic growth of data volume takes challenge to network traffic classification. Therefore, using feature selection methods for multimedia flow identification and classification is particularly important in the big data era. This paper introduces related works on feature selection using identification and categorization of multimedia traffic, which is divided into three categories：Filter, Wrapper, Embedded and analyzes the performance of these methods. Then, this paper compares the performance of various feature selection algorithms using latest dataset from three aspects：The running speed, the feature compression rate and the feature selection accuracy. Besides, to improve classification accuracy, this paper proposes a hierarchical structure to reach fine-grained classification, according to the dataset.

Key words: features selection, video traffic classification, hierarchical classifier