Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction
With the evolution of cellular networks and wireless-local-area-network-based communication technologies, services for smart device users have appeared. With the popularity of 4G and 5G, smart device users can now consume larger bandwidths than before. Consequently, the demand for various services,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/22/10490 |
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| author | Jeonghun Woo Seungwoo Hong Donghyun Kang Donghyeok An |
| author_facet | Jeonghun Woo Seungwoo Hong Donghyun Kang Donghyeok An |
| author_sort | Jeonghun Woo |
| collection | DOAJ |
| description | With the evolution of cellular networks and wireless-local-area-network-based communication technologies, services for smart device users have appeared. With the popularity of 4G and 5G, smart device users can now consume larger bandwidths than before. Consequently, the demand for various services, such as streaming, online games, and video conferences, has increased. For improved quality of experience (QoE), streaming services utilize adaptive bitrate (ABR) algorithms to handle network bandwidth variations. ABR algorithms use network bandwidth history for future network bandwidth prediction, allowing them to perform efficiently when network bandwidth fluctuations are minor. However, in environments with frequent network bandwidth changes, such as wireless networks, the QoE of video streaming often degrades because of inaccurate predictions of future network bandwidth. To address this issue, we utilize the gated recurrent unit, a time series prediction model, to predict the network bandwidth accurately. We then propose a buffer-based ABR streaming technique that selects optimized video-quality settings on the basis of the predicted bandwidth. The proposed algorithm was evaluated on a dataset provided by Zeondo by categorizing instances of user mobility into walking, bus, and train scenarios. The proposed algorithm improved the QoE by approximately 11% compared with the existing buffer-based ABR algorithm in various environments. |
| format | Article |
| id | doaj-art-a6a16a93f98b4d7c9ed0ff99f9240a06 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-a6a16a93f98b4d7c9ed0ff99f9240a062025-08-20T01:53:49ZengMDPI AGApplied Sciences2076-34172024-11-0114221049010.3390/app142210490Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth PredictionJeonghun Woo0Seungwoo Hong1Donghyun Kang2Donghyeok An3Department of Computer Engineering, Changwon National University, Changwon 51140, Republic of KoreaNetwork Research Department, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of KoreaDepartment of Computer Engineering, College of IT Convergence, Gachon University, Seongnam-si 13120, Republic of KoreaDepartment of Computer Engineering, Changwon National University, Changwon 51140, Republic of KoreaWith the evolution of cellular networks and wireless-local-area-network-based communication technologies, services for smart device users have appeared. With the popularity of 4G and 5G, smart device users can now consume larger bandwidths than before. Consequently, the demand for various services, such as streaming, online games, and video conferences, has increased. For improved quality of experience (QoE), streaming services utilize adaptive bitrate (ABR) algorithms to handle network bandwidth variations. ABR algorithms use network bandwidth history for future network bandwidth prediction, allowing them to perform efficiently when network bandwidth fluctuations are minor. However, in environments with frequent network bandwidth changes, such as wireless networks, the QoE of video streaming often degrades because of inaccurate predictions of future network bandwidth. To address this issue, we utilize the gated recurrent unit, a time series prediction model, to predict the network bandwidth accurately. We then propose a buffer-based ABR streaming technique that selects optimized video-quality settings on the basis of the predicted bandwidth. The proposed algorithm was evaluated on a dataset provided by Zeondo by categorizing instances of user mobility into walking, bus, and train scenarios. The proposed algorithm improved the QoE by approximately 11% compared with the existing buffer-based ABR algorithm in various environments.https://www.mdpi.com/2076-3417/14/22/10490buffer-based ABRquality of experiencebandwidth predictiongated recurrent unitvideo streaming |
| spellingShingle | Jeonghun Woo Seungwoo Hong Donghyun Kang Donghyeok An Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction Applied Sciences buffer-based ABR quality of experience bandwidth prediction gated recurrent unit video streaming |
| title | Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction |
| title_full | Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction |
| title_fullStr | Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction |
| title_full_unstemmed | Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction |
| title_short | Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction |
| title_sort | improving the quality of experience of video streaming through a buffer based adaptive bitrate algorithm and gated recurrent unit based network bandwidth prediction |
| topic | buffer-based ABR quality of experience bandwidth prediction gated recurrent unit video streaming |
| url | https://www.mdpi.com/2076-3417/14/22/10490 |
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