用于多层边缘/云视频流服务的编排架构

E. S. Gama, Natesha B V, R. Immich, L. Bittencourt
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引用次数: 0

摘要

视频流已经成为一种流行的娱乐形式和重要的通信手段,但在互联网上提供高质量的视频内容面临着许多挑战。其中一个关键挑战是不同的网络条件会显著影响视频流质量,例如带宽波动和数据包丢失。为了克服这些挑战,需要一种自适应视频流架构来实时调整视频流,以适应不断变化的网络条件,并确保最终用户的高体验质量(QoE)。本文介绍了MIGRATE,这是一种用于视频流服务的编排器体系结构,能够实时适应用户需求。该研究考虑了边缘/云多层网络基础设施。此外,提出了一个整数线性规划(ILP)模型和贪心解来确定用户与服务之间的连接分布。实验结果表明,基于所使用的优化策略,可以观察到所使用的资源与提供给用户的QoE之间存在权衡。此外,我们还讨论了在设计视频流系统时考虑QoE指标和用户参与度的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Orchestrator Architecture for Multi-tier Edge/Cloud Video Streaming Services
Video streaming has become a prevalent form of entertainment and a vital means of communication, but the challenges of delivering high quality video content over the internet are numerous. One of the key challenges is the varying network conditions that can significantly impact video streaming quality, such as bandwidth fluctuations and packet loss. To overcome these challenges, an adaptive video streaming architecture is needed to adjust the video streaming in real-time to match the changing network conditions and ensure a high Quality of Experience (QoE) for the end-user. This article presents MIGRATE, an orchestrator architecture for video streaming services capable of adapting to user demand in real-time. The study considers an edge/cloud multi-tier network infrastructure. In addition, an Integer Linear Programming (ILP) model and a Greedy solution are proposed to decide the distribution of connections between users and services. Experimental results show that based on the optimization strategy used, it is observed that there is a trade-off between the resources used and the QoE provided to users. Further, we discuss the importance of considering QoE metrics and user engagement in designing video streaming systems.
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