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A Novel Deep Learning Method for Application Identification in Wireless Network
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DOI：10.1109/CC.2018.8485470.png)
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Abstract
En 中文
In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In that case, the Quality of Experience (QoE) has received much attention and has become a key performance measurement for the application and service. In order to meet the users' expectations, the management of the resource is crucial in wireless network, especially the QoE based resource allocation. One of the effective way for resource allocation management is accurate application identification. In this paper, we propose a novel deep learning based method for application identification. We first analyse the requirement of managing QoE for wireless communication, and review the limitation of the traditional identification methods. After that, a deep learning based method is proposed for automatically extracting the features and identifying the type of application. The proposed method is evaluated by using the practical wireless traffic data, and the experiments verify the effectiveness of our method.
Keywords:
quality of experience
application identification
protocol identification
deep learning
feature extraction
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