• 网络与通信 •

### 基于分数布朗运动的自相似流量判别及生成方法

1. 1. 北京工业职业技术学院 信息中心，北京 100042
2. 国防大学 信息作战与指挥训练教研部，北京 100091
3. 北京航空航天大学 可靠性与系统工程学院，北京 100191
• 收稿日期:2012-10-12 修回日期:2012-11-30 出版日期:2013-04-01 发布日期:2013-04-23
• 通讯作者: 张雪媛
• 作者简介:张雪媛(1978-)，女，江苏泗洪人，工程师，硕士，主要研究方向：计算机网络、数据挖掘；王永刚(1976-)，男，江苏泗洪人，讲师，硕士，主要研究方向：计算机网络、指挥自动化；张琼(1989-)，女，河南驻马店人，硕士研究生，主要研究方向：网络可靠性。

### Self-similar traffic discrimination and generating methods based on fractal Brown motion

ZHANG Xueyuan1,WANG Yonggang2,ZHANG Qiong3

1. 1. Information Center, Beijing Polytechnic College, Beijing 100042, China
2. Department of Information War and Command Training, National Defense University, Beijing 100091, China
3. School of Reliability and Systems Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
• Received:2012-10-12 Revised:2012-11-30 Online:2013-04-01 Published:2013-04-23
• Contact: ZHANG Xueyuan

Abstract: To deal with the difficulties of lacking the discrimination method of network's traffic self-similarity and producing negative traffic based on classical Fractal Brown Motion (FBM), a discrimination method was proposed based on multiple order moment and a generation method was provided based on modified FBM model. Firstly, the mathematical formula of sample moment was studied. The discrimination method of self-similarity traffic was obtained on account of fractal moment analysis. Secondly, the classical Random Midpoint Displacement (RMD) algorithm was modified. At last, taking account of the real traffic of Bellcore and LBL, the discrimination method and generation method were given. The comparison of the simulation results with the actual experimental data proves that the method is feasible.