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Software‐defined information‐centric networking based exercise intensity evaluation of volleyball player: An efficient convolutional neural network method
Author(s) -
Ban Yunqiang
Publication year - 2020
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.246
Subject(s) - computer science , software defined networking , router , software , convolutional neural network , artificial neural network , computer network , intensity (physics) , multimedia , artificial intelligence , physics , quantum mechanics , programming language
The exercise intensity evaluation has been accepted as a research hotspot in the field of body area network, where the data collection plays the considerably important role. In this letter, the exercise intensity evaluation of volleyball player is conducted based on two emerging networking paradigms, that is, Software‐Defined Networking (SDN) and Information‐Centric Networking (ICN). To be specific, SDN is used to monitor the exercise intensity data via the functions of centralized control and global network view; at the same time, ICN router is responsible for storing the important and frequently used exercise intensity data via the ability of in‐network caching. In addition, Convolutional Neural Network (CNN) model is exploited to train the exercise intensity data and further to conduct the behaviors of volleyball player. The experimental results show that the proposed evaluation method is efficient.