Machine Learning-based Stable P2P IPTV Overlay
نویسندگان
چکیده
Live video streaming is one of the newly emerged services over Internet that has attracted immense interest service providers. Since was not designed for such during its inception, a poses some serious challenges including cost and scalability. Peer-to-Peer (P2P) Protocol Television (IPTV) an application-level distributed paradigm to offer live contents. In terms ease deployment, it as alternative client server, Content Delivery Network (CDN) IP multicast solutions. Nevertheless, P2P approach struggled provide desired quality due number issues. Stability peers in network major issues among these. Most existing approaches address this issue through older-stable principle. This paper first extensively investigates principle observe validity different scenarios. It observed does hold several them. Then, utilizes machine learning predict stability peers. work evaluates accuracy algorithms prediction stability, where Gradient Boosting Regressor (GBR) out-performs other algorithms. Finally, presents proof-of-concept simulation compare effectiveness rule learning-based predictions stabilization overlay. The results indicate estimation significantly improves system.
منابع مشابه
Construction of attack-resilient and efficient overlay topologies for large-scale P2P-based IPTV infrastructures
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ژورنال
عنوان ژورنال: Computers, materials & continua
سال: 2022
ISSN: ['1546-2218', '1546-2226']
DOI: https://doi.org/10.32604/cmc.2022.024116