A game theoretic approach to video streaming over peer-to-peer networks

Ehsan Maani; Aggelos K Katsaggelos

doi:10.1109/ICIP.2010.5652666

A game theoretic approach to video streaming over peer-to-peer networks

Ehsan Maani^*, Aggelos K Katsaggelos

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

We address the problem of content-aware, foresighted resource reciprocation for media streaming over peer-to-peer (P2P) networks. The envisioned P2P network consists of autonomous and self-interested peers trying to maximize their individual utilities. The resource reciprocation among such peers is modeled as a stochastic game and peers determine the optimal strategies for resource reciprocation using a Markov Decision Process (MDP) framework. Unlike existing solutions, this framework takes the content and the characteristics of the video signal into account by introducing an artificial currency in order to maximize the video quality in the entire network.

Original language	English (US)
Title of host publication	2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages	2909-2912
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2010.5652666
State	Published - Dec 1 2010
Event	2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong Duration: Sep 26 2010 → Sep 29 2010

Other

Other	2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/Territory	Hong Kong
City	Hong Kong
Period	9/26/10 → 9/29/10

Keywords

Game theory
P2P multimedia sharing

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.2010.5652666

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abstract = "We address the problem of content-aware, foresighted resource reciprocation for media streaming over peer-to-peer (P2P) networks. The envisioned P2P network consists of autonomous and self-interested peers trying to maximize their individual utilities. The resource reciprocation among such peers is modeled as a stochastic game and peers determine the optimal strategies for resource reciprocation using a Markov Decision Process (MDP) framework. Unlike existing solutions, this framework takes the content and the characteristics of the video signal into account by introducing an artificial currency in order to maximize the video quality in the entire network.",

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AB - We address the problem of content-aware, foresighted resource reciprocation for media streaming over peer-to-peer (P2P) networks. The envisioned P2P network consists of autonomous and self-interested peers trying to maximize their individual utilities. The resource reciprocation among such peers is modeled as a stochastic game and peers determine the optimal strategies for resource reciprocation using a Markov Decision Process (MDP) framework. Unlike existing solutions, this framework takes the content and the characteristics of the video signal into account by introducing an artificial currency in order to maximize the video quality in the entire network.

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A game theoretic approach to video streaming over peer-to-peer networks

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Keywords

ASJC Scopus subject areas

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