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Identifying High-Rate Flows Based on Sequential Sampling

文献类型：期刊论文

作者Zhang, Yu1,2; Fang, Binxing1,2; Luo, Hao2
刊名IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
出版日期2010-05-01
卷号E93D期号:5页码:1162-1174
关键词traffic monitoring high-rate flow identification sequential sampling
ISSN号0916-8532
DOI10.1587/transinf.E93.D.1162
英文摘要We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling. TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.
资助项目National Natural Science Foundation of China[60703021] ; National High-Tech Development 863 Program of China[2007AA010501] ; National High-Tech Development 863 Program of China[2007AA01Z444] ; National High-Tech Development 863 Program of China[2007AA01Z406] ; National High-Tech Development 863 Program of China[2009AA012437]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000279136500025
出版者IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
源URL[http://119.78.100.204/handle/2XEOYT63/12513]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhang, Yu
作者单位1.Harbin Inst Technol, Res Ctr Comp Network & Informat Secur Technol, Harbin 150001, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yu,Fang, Binxing,Luo, Hao. Identifying High-Rate Flows Based on Sequential Sampling[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,2010,E93D(5):1162-1174.
APA Zhang, Yu,Fang, Binxing,&Luo, Hao.(2010).Identifying High-Rate Flows Based on Sequential Sampling.IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,E93D(5),1162-1174.
MLA Zhang, Yu,et al."Identifying High-Rate Flows Based on Sequential Sampling".IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS E93D.5(2010):1162-1174.

入库方式： OAI收割

来源：计算技术研究所

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