Northampton Electronic Collection of Theses and Research

Deep Learning Approach for Real-time Video Streaming Traffic Classification

Jameel, M. A., Turner, S., Kanakis, T., Al-Sherbaz, A. and Bhaya, W. S. (2022) Deep Learning Approach for Real-time Video Streaming Traffic Classification. In: 2022 International Conference on Computer Science and Software Engineering (CSASE) :. IRQ: IEEE. pp. 168-174.

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Al_Jameel_etal_IEEE_2022_Deep_Learning_Approach_for_Real-time_Video_Streaming_Traffic_Classification
Al_Jameel_etal_IEEE_2022_Deep_Learning_Approach_for_Real_time_Video_Streaming_Traffic_Classification.pdf - Accepted Version
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Information
Abstract:
Video streaming services such as Amazon Prime Video, Netflix and YouTube continue to be of enormous demand in everyday peoples' lives. This enticed research into new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Then, data was pre-processed to select the desired features for video traffic classification. Based on the performance evaluation, the model produces an overall accuracy of 99.3% when classifying video streaming traffic using a multi-layer feedforward neural network. This paper also evaluates the DL approach's effectiveness compared to the Gaussian Naive Bayes algorithm (GNB), one of the most well-known machine learning techniques used in Internet traffic classification. The model is promising to be applied in a real-time scenario as it showed its ability to predict new unseen data with 98.4 % overall accuracy.
Creators:
Jameel, M. A., Turner, S., Kanakis, T., Al-Sherbaz, A. and Bhaya, W. S.
Publisher:
IEEE
Faculties, Divisions and Institutes:
Faculties > Faculty of Arts, Science & Technology > Computing
Date:
25 April 2022
Date Type:
Publication
Page Range:
pp. 168-174
Title of Book:
2022 International Conference on Computer Science and Software Engineering (CSASE) :
Series Name:
2022 International Conference on Computer Science and Software Engineering (CSASE)
Event Title:
International Conference on Computer Science and Software Engineering (CSASE)
Event Dates:
2022-03-15 - 2022-03-17
Place of Publication:
IRQ
Event Location:
University of Duhok
Language:
English
ISBN:
9781665426336
DOI:
10.1109/csase51777.2022.9759644
Status:
Published / Disseminated
Refereed:
Yes
Related URLs:
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