[1]谢逸,唐成华,黄向农.双层隐马尔可夫链的突发流合成[J].智能系统学报,2012,7(02):108-114.
 XIE Yi,TANG Chenghua,HUANG Xiangnong.A doubly hidden Markov model for synthesizing bursty workloads[J].CAAI Transactions on Intelligent Systems,2012,7(02):108-114.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第7卷
期数:
2012年02期
页码:
108-114
栏目:
出版日期:
2012-04-25

文章信息/Info

Title:
A doubly hidden Markov model for synthesizing bursty workloads
文章编号:
1673-4785(2012)02-0108-07
作者:
谢逸1唐成华2黄向农3
1.中山大学 信息科学与技术学院,广东 广州 510006;
2. 桂林电子科技大学, 计算机科学与工程学院,广西 桂林 541004;
3. 中山大学 网络与信息技术中心,广东 广州 510275
Author(s):
XIE Yi1 TANG Chenghua2 HUANG Xiangnong3
1. School of Information Science and Technology, Sun YatSen University,Guangzhou 510006, China;
2. School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin 541004, China;
3. Network and Information Technology Center, Sun YatSen University, Guangzhou 510275, China
关键词:
隐马尔可夫模型合成突发流网络
Keywords:
hidden Markov model synthesize burst workload network
分类号:
TP30
文献标志码:
A
摘要:
网络流模型被广泛用于构建网络与网络服务的测试环境,其准确性直接影响各种业务的性能评估结果及在实际网络环境中的鲁棒性.随着电子商务及新型网络应用的普及,突发流现象已经成为现代互联网的主要特征之一.针对平稳网络流而设计的传统网络流模型已经难以有效地描述现代网络中突发流的时间结构性及统计属性,从而不能准确反映现代网络流的行为特征.为此,提出一种新的结构化双层隐马尔可夫模型用于模拟实际网络环境下的突发流,并设计了有效的模型参数推断算法及突发流合成方法.该模型通过结构化的2层隐马尔可夫过程描述突发流并实现仿真合成,使合成流可以重现实际突发流的时间结构性、统计特性及自相似性.实验表明,该模型可以有效合成突发流.
Abstract:
Network traffic models have been widely used to build the test environment for networks and network services. Their accuracy directly impacts the performance evaluation results of various services and their robustness in the actual network environment. With the popularity of ecommerce and new network applications, the burst traffic phenomenon has become one of the main features of the modern internet. Traditional traffic models designed for stationary network traffic have difficulty in effectively describing the temporal structure and statistical properties of burst traffic of modern networks, which causes them not to be able to accurately reflect the actual network environment. In this paper, a new structural doubly hidden Markov model was proposed to characterize the practical burst traffic in a real network environment. Efficient algorithms for inference of model parameters and synthesis of the burst workload were also introduced. Based on the hierarchical structure, the proposed model can reproduce the similar temporal structure, statistical properties, and selfsimilarity of the real burst traffic. The proposed model includes two hidden Markov processes. The parent Markov state process was used to describe the largescale trends or phases of burst traffic. The child Markov process was used to describe the smallscale fluctuations that happen during a given phase of the arrival process. Experiments were implemented to validate the proposed model.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2011-11-14.
网络出版日期:2012-03-09.
基金项目:国家自然科学基金资助项目(60970146);教育部博士点专项基金资助项目(20090171120001);中央高校基本科研业务费专项资金资助项目(11lgpy38).
通信作者:谢逸.            E-mail:xieyi5@mail.sysu.edu.cn.
作者简介:
谢逸,男,1973年生,讲师,博士,主要研究方向为计算机网络与通信.发表学术论文20余篇,其中多篇被SCI、EI检索.
 唐成华,男,1974年生,副教授,博士,主要研究方向为智能信息处理、网络信息安全等,发表学术论文30余篇,被EI检索13篇.
黄向农,男,1958年生,工程师,主要研究方向为计算机网络应用技术.
更新日期/Last Update: 2012-07-12