Peer-to-Peer Live Streaming with Recommender Systems
Analysis of optimal load distribution in P2P networks with recommendation algorithms
Studied the theoretical and practical aspects of peer-to-peer live streaming systems enhanced with recommender systems. The work involved deriving optimal peer load distributions and analyzing asymptotic behavior when recommenders suggest channel switching to improve viewing experience.
Key Research Questions:
- What is the optimal load distribution across P2P peers?
- How do recommender systems affect overall system stability?
- What are the asymptotic performance boundaries?
Contributions:
- Analytical framework for P2P system optimization
- Load distribution theory with recommender integration
- Asymptotic behavior characterization
Relevance: P2P systems remain important for content delivery networks, and this analysis provides insights for designing scalable, recommendation-aware streaming systems.