TITLE:
Self Similarity Analysis of Web Users Arrival Pattern at Selected Web Centers
AUTHORS:
Pushpalatha Sarla, Mallikarjuna Reddy Doodipala, Manohar Dingari
KEYWORDS:
Long-Range Dependence, Self-Similarity, Poisson Process, Percentiles, Hurst Parameter
JOURNAL NAME:
American Journal of Computational Mathematics,
Vol.6 No.1,
March
4,
2016
ABSTRACT: The paper focuses on
measuring self-similarity using few techniques by an index called Hurst index which
is a self-similarity parameter. It has been evident that Internet traffic
exhibits self-similarity. Motivated by this fact, real time web users at
various centers considered here as traffic and it has been examined by various
methods to test the self-similarity. The results from the experiments carried
out verify that the traffic examined in the present study is self similar using
a new method based on some descriptive measures; for example percentiles have
been applied to compute Hurst parameter which gives intensity of the
self-similarity. Numerical results and analysis we discussed and presented here
play a significant role to improve the services at web centers in the view of
quality of service (QOS).