Date of Award


Publication Type

Master Thesis

Degree Name



Computer Science

First Advisor

Aggarwal, Akshaikumar (School of Computer Science)


Computer Science.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


Estimating available bandwidth accurately is extremely important for many network related applications, especially the ones which need real-time traffic information. With the ever increasing use of Internet, several available bandwidth measurement techniques have been proposed. But most of them assume fluid traffic model, whereas studies show that current Internet traffic follows Poisson distribution. Moreover, very few can operate in stand-alone mode and have relatively high estimation errors. We propose a new method, PathAB, which combines the concepts of three existing algorithms, MoSeab, PoissonProb and PathChirp. It first obtains a rough estimation of available bandwidth using an exponential probing train, and later obtains the final estimate using several Poisson distributed probing trains. It can operate both in client-server and stand-alone modes. Unlike other stand-alone methods, PathAB sends very small echo packets back-to-back after the large probe packets to reduce the cross-traffic effect in returning path as well as the estimation error.