A Versatile Probability Distribution for Light and Heavy Tails of Web File Sizes

Author

Chlebus, Edward ; Divgi, Gautam

Author_Institution

Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL

fYear

2009

fDate

5-8 April 2009

Firstpage

1

Lastpage

7

Abstract

A novel unique probability distribution, which has a lognormal body and either light or heavy tail, has been fitted to various empirical data sets of Web file sizes. The optimal parameters of this distribution have been determined by the maximum likelihood estimation combined with the optimization algorithm minimizing a goodness-of-fit metric specially adopted to provide the best fit to the upper tail. The mirror transformation of the processed original data set with respect to the median has been proposed to improve the fit. The obtained results question the common opinion that the probability distribution of Web file sizes is heavy-tailed. The lognormal fits are given for comparison.

Keywords

Internet; log normal distribution; maximum likelihood estimation; optimisation; Web file size; goodness-of-fit metric minimization; heavy tail; lognormal body; maximum likelihood estimation; optimization algorithm; versatile probability distribution; Communications Society; Computer science; IP networks; Internet; Maximum likelihood estimation; Mirrors; Peer to peer computing; Probability distribution; Telecommunication traffic; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications and Networking Conference, 2009. WCNC 2009. IEEE

Conference_Location

Budapest

ISSN

1525-3511

Print_ISBN

978-1-4244-2947-9

Electronic_ISBN

1525-3511

Type

conf

DOI

10.1109/WCNC.2009.4917551

Filename

4917551