Using Hidden Markov Chains for Modeling P2P-TV Traffic

Author

Garcia, Maria Antonieta ; Da Silva, Ana Paula Couto ; Meo, Michela

Author_Institution

Politec. di Torino, Torino, Italy

fYear

2010

fDate

6-10 Dec. 2010

Firstpage

1

Lastpage

6

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.

Keywords

Markov processes; peer-to-peer computing; telecommunication computing; telecommunication traffic; television broadcasting; P2P-TV applications; P2P-TV traffic modeling; PPLive; SopCast; hidden Markov chains; network planning; traffic engineering; Bandwidth; Correlation; Generators; Hidden Markov models; Peer to peer computing; Streaming media; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference (GLOBECOM 2010), 2010 IEEE

Conference_Location

Miami, FL

ISSN

1930-529X

Print_ISBN

978-1-4244-5636-9

Electronic_ISBN

1930-529X

Type

conf

DOI

10.1109/GLOCOM.2010.5683368

Filename

5683368