This is a collection of papers talking about internet resource allcation by machine learning.
According to the cisco report, the requirement of internet resource is growing rapidly.
Thus, a optimal resource allcatino scheme would provde the highest utility in limited resource.
However, resource allocation is a very complex problem.
And we know the machine learning is a very popular way to solve this kinds of problems.
In my research, I want to find a optimal resource allcation policy for the internet by machine learning.
The sharing references here is for research. If any authors do not want their paper to be listed here, please contact Chen-Po Chen. (Email: cpchen840108@gmail.com)
- A Study of Deep Learning Networks on Mobile Traffic Forecasting by C.-W. Huang, C.-T. Chiang, and Q. Li. (source code)
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From 4g to 5g: Self-organized network management meets machine learning by MOYSEN, Jessica; GIUPPONI, Lorenza. arXiv preprint arXiv, 2017
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Mobile Traffic Forecasting for Maximizing 5G Network Slicing Resource Utilization by Sciancalepore, Vincenzo, et al. IEEE INFOCOM, 2017
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Resource Management with Deep Reinforcement Learning by Mao, Hongzi, et al. HotNets, 2016
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Learning radio resource management in 5G networks: Framework, opportunities and challenges by Calabrese, Francesco D., et al. arXiv, 2016
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Optimizing the Power Consumption of Mobile Networks Based on Traffic Prediction by S. Dawoud, A. Uzun, S. Göndör and A. Küpper, IEEE 38th Annual Computer Software and Applications Conference, 2014