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) |
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Title of host publication | 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings |
Pages | 2909-2912 |
Number of pages | 4 |
DOIs | |
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 |
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Country | 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