Multi-access Edge Computing for Adaptive Bitrate Video Streaming

Jesus Aguilar-Armijo
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Abstract

Video streaming is the most used service in mobile networks and its usage will continue growing in the upcoming years. Due to this increase, content delivery should be improved as a key aspect of video streaming service, supporting higher bandwidth demand while assuring high quality of experience (QoE) for all the users. Multi-access edge computing (MEC) is an emerging paradigm that brings computational power and storage closer to the user. It is seen in the industry as a key technology for 5G mobile networks, with the goals of reducing latency, ensuring highly efficient network operation, improving service delivery and offering an improved user experience, among others. In this doctoral study, we aim to leverage the possibilities of MEC to improve the content delivery of video streaming services. We present four main research questions to target the different challenges in content delivery for HTTP Adaptive Streaming.
自适应比特率视频流的多访问边缘计算
视频流是移动网络中使用最多的服务,它的使用将在未来几年继续增长。由于这种增长,内容交付应该作为视频流服务的一个关键方面得到改进,以支持更高的带宽需求,同时确保所有用户的高质量体验(QoE)。多访问边缘计算(MEC)是一种新兴的范例,它使计算能力和存储更接近用户。在业内,它被视为5G移动网络的关键技术,其目标是减少延迟,确保高效的网络运营,改善服务交付和提供更好的用户体验等。在这项博士研究中,我们的目标是利用MEC的可能性来改善视频流媒体服务的内容交付。我们提出了四个主要的研究问题,以针对HTTP自适应流的内容交付中的不同挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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