By Topic

Model-based real-time volume control for interactive network traffic replay

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

4 Author(s)
Weibo Chu ; MOE KLINNS Lab., Xian Jiaotong Univ., Xian, China ; Xiaohong Guan ; Lixin Gao ; Zhongmin Cai

Traffic volume control is one of the fundamental requirements in traffic generation and transformation. However, due to the complex interactions between the generated traffic and replay environment (delay, packet loss, connection blocking, etc), controlling traffic volume in interactive network traffic replay becomes a challenging problem. In this paper, we present a novel model-based analytical method to address this problem where the generated traffic volume is regulated through adjustment of input traffic volume. By analyzing the replay mechanism in terms of how packets are processed, and properly choosing buffered packets amount and to-be-received packets amount as system states, we present a novel model-based analytical method to obtain the desired input volume. The traffic volume control problem is then converted to a state prediction problem where we employ Recursive Least Square (RLS) filter to predict system states. As compared to other adaptive control techniques, our method does not involve any learning scheme and hence completely requires no convergence time. Experimental studies further indicate that our method is efficient in tracking target traffic volume (both static and time-varying) and works under a wide range of network conditions.

Published in:

Network Operations and Management Symposium (NOMS), 2012 IEEE

Date of Conference:

16-20 April 2012