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Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing
2018
IEICE transactions on communications
Akihiro NAKAO †a) and Ping DU †b) , Members SUMMARY In this paper, we posit that, in future mobile network, network softwarization will be prevalent, and it becomes important to utilize deep machine learning within network to classify mobile traffic into fine grained slices, by identifying application types and devices so that we can apply Quality-of-Service (QoS) control, mobile edge/multi-access computing, and various network function per application and per device. This paper reports our
doi:10.1587/transcom.2017cqi0002
fatcat:b24n5zc46vboxnbzsnntl3sfqu