DocumentCode :
3391232
Title :
Stochastic Sampling for Internet Traffic Measurement
Author :
Wolf, Tilman ; Cai, Yan ; Kelly, Patrick ; Gong, Weibo
Author_Institution :
Dept. of Electr. & Comput. Eng., Massachusetts Univ., Amherst, MA
fYear :
2007
fDate :
11-11 May 2007
Firstpage :
31
Lastpage :
36
Abstract :
The increasing complexity of the Internet demands continued improvements to measurement techniques and data analysis methods to aid our understanding of network operation. The availability of accurate measurement data is necessary in many areas ranging from attack detection, novel pricing schemes, buffer dimensioning and switch design to general network management. In this paper, we develop a theory for accurate and unbiased Internet traffic measurement using the tools of Poisson random sampling. We show how this approach helps in storing, managing, and aggregating data from different sources with independent clocks and sampling rates. We present results that show that stochastic sampling maintains important information about network measurements that would be lost when using conventional uniform sampling.
Keywords :
Internet; computer network management; random processes; sampling methods; stochastic processes; telecommunication traffic; Internet traffic measurement; Poisson random sampling; attack detection; buffer dimensioning; data analysis methods; general network management; network operation; novel pricing schemes; stochastic sampling; switch design; Area measurement; Data analysis; IP networks; Internet; Measurement techniques; Pricing; Sampling methods; Stochastic processes; Switches; Telecommunication traffic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IEEE Global Internet Symposium, 2007
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-1697-4
Type :
conf
DOI :
10.1109/GI.2007.4301427
Filename :
4301427
Link To Document :
بازگشت