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Adaptive video streaming solution based on multi-access edge computing advantages
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AI
DOI：10.1007/s11042-023-17764-x.png)
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Abstract
En 中文
In the last few years, video streaming traffic surpassed all the other Internet traffic. This is mainly due to the substantial and ever-increasing size of video files and the widespread popularity of streaming services. A significant portion of the traffic above originates from mobile devices, thereby increasing demands on operators' infrastructures and potentially degrading services. The content providers' response has been to adopt adaptive video streaming techniques that avoid playback interruptions, as these interruptions are the leading cause of the deterioration in the Quality Of Experience (QoE). To go beyond end-to-end approaches, the authors proposed a new strategy that utilizes the Multi-access Edge Computing (MEC) standard to optimize streaming services. Being located at the MEC level allows, indeed, to be aware of the network congestion's state, which facilitates optimizing network operations. The suggested seamless strategy considers the users' devices' parameters to prevent them from selecting video quality options that would not enhance their viewing experience. By avoiding choices that could diminish the quality or worsen the experience, our strategy optimizes network resources and reduces energy and bandwidth consumption on the mobile device side. The proposed approach was implemented and tested within an emulation environment. The findings demonstrate the suitability of this type of approach in comparison with existing strategies (YouTube service) in terms of users' satisfaction and network performance.
Keywords:
Dynamic adaptive video streaming
Multi-access Edge Computing (MEC)
QoE
Optimization
Congestion
User terminal
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W
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