Using Hidden Markov Chains for Modeling P2P-TV Traffic

Abstract

The increasing success of P2P-TV applications, that may overwhelm the network with their large volume of traffic in the near future, calls for the need of new traffic models that can effectively represent the traffic generated by these applications. In this paper, we study the traffic generated by PPLive and SopCast, that are among the most popular P2P-TV applications of today, and propose Hidden-Markov chains for modeling the traffic they generate. Our results show that the models are quite accurate and can be effectively used in many networking tasks such as network performance analysis, network planning and dimensioning, traffic engineering.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.1109/GLOCOM.2010.5683368

• http://xplorestaging.ieee.org/ielx5/5682081/5683069/05683368.pdf?arnumber=5683368,

http://dx.doi.org/10.1109/glocom.2010.5683368

• https://dblp.uni-trier.de/db/conf/globecom/globecom2010.html#GarciaSM10,

http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005683368,

https://iris.polito.it/handle/11583/2557573,

http://porto.polito.it/2557573,

https://academic.microsoft.com/#/detail/2092994810