Cart (Loading....) | Create Account
Close category search window

An adaptive statistical sampling technique for computer network traffic

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Dogman, A. ; Fac. of Art, Comput., Eng. & Sci., Sheffield Hallam Univ., Sheffield, UK ; Saatchi, R. ; Al-Khayatt, S.

The rapid growth of real-time applications transmitted over multimedia networks, makes measurement of their generated traffic increasingly important. These measurements allow the quality of service (QoS) provided by the network for the transmission of the applications to be assessed. However, most real-time applications generate an extensive amount of traffic data. Analysing these data in real-time is computationally intensive. Therefore, in order to reduce the amount of processed data, sampling needs to be performed. In fixed rate sampling, the sample rate is unaffected by the packet transmission rate. However, it is advantageous to adapt the sample rate in relation to packet transmission rate. In this study a novel statistical adaptive sampling method has been developed. The method adaptively adjusts the time interval between two consecutive sampled sections (called pre-and post sampling sections). This time interval is decreased when the two sections significantly differ statistically and it is increased when their net statistic is within a predefined threshold. The operation of the developed sampling method was evaluated using a simulated computer network. The results demonstrated the effectiveness of the method in various scenarios, however more work is in progress to make the method more robust.

Published in:

Communication Systems Networks and Digital Signal Processing (CSNDSP), 2010 7th International Symposium on

Date of Conference:

21-23 July 2010

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.