Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

A New Method for Measuring Packet Loss Probability Using a Kalman Filter

By: Ionescu, D.; Dongli Zhang;

2009 / IEEE

Description

This item was taken from the IEEE Periodical ' A New Method for Measuring Packet Loss Probability Using a Kalman Filter ' In this paper, a new packet loss probability (PLP) estimation method is developed based on the Kalman estimation procedure. The Kalman filter is used for the optimal and recursive estimation of the network traffic mean and standard deviation. The estimation is obtained from past measurements to calculate the one-step prediction and is then applied to calculate the PLP parameter with the large-buffer-based estimation formula based on the large deviation theory. The algorithm recursively runs and is applied for the online packet loss control loop, which keeps the PLP parameter under the limit negotiated in the service level agreement with the customer by the Internet service provider. A series of experiments were conducted to evaluate its performance on the live NCIT*net2 network under different traffic arrival models, for two different aggregated traffic rates and different buffer sizes. The numeric results presented in this paper demonstrate the accuracy and effectiveness of the algorithms introduced.