CAJ | 학술논문

该文提出一种基于改进隐马尔可夫(Hidden Markov Model, HMM)的多媒体业务分类算法。改进后的算法保持典型 HMM 模型结构不变，通过区分包大小的位置信息，改变发射概率取值，提高了多媒体业务区分性能。理论分析表明，该文模型在计算量上低于高阶HMM；实验结果表明，改进的HMM多媒体业务分类算法的区分效果优于现有的HMM多媒体业务分类方法。
해문제출일충기우개진은마이가부(Hidden Markov Model, HMM)적다매체업무분류산법。개진후적산법보지전형 HMM 모형결구불변，통과구분포대소적위치신식，개변발사개솔취치，제고료다매체업무구분성능。이론분석표명，해문모형재계산량상저우고계HMM；실험결과표명，개진적HMM다매체업무분류산법적구분효과우우현유적HMM다매체업무분류방법。
This paper proposes an improved Hidden Markov Model (HMM) based multimedia traffic classification method. This method preserves the classical HMM model structure, and improves the performance of multimedia traffic classification by changing the emitting probability value with the position information of packet size. Theoretical analysis indicates that the new model can reduce the computational complexity of the classical HMM model. Simulation results show that the proposed method can improve the classification performance compared with the existing HMM based classification method.