Using machine learning for dynamic multicast capacity planning

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Abstract

We are using service consumption data from BT’s UK–wide IPTV service to identify main drivers of network capacity and to predict changes on the level of exchanges. We have used a decision tree to identify main drivers and find that provisioning data is sufficient to identify capacity requirements for cable links to exchanges. We have used cluster analysis to identify changes in service consumption and to construct an early warning system for potential capacity bottlenecks.

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APA

Karthikeyan, V., Nauck, D. D., & Rio, M. (2017). Using machine learning for dynamic multicast capacity planning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10630 LNAI, pp. 417–422). Springer Verlag. https://doi.org/10.1007/978-3-319-71078-5_36

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