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QoS monitoring in real-time streaming overlays based on lock-free data structures

机译:基于锁定数据结构的实时流覆盖QoS监控

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摘要

Peer-to-peer streaming is a well-known technology for the large-scale distribution of real-time audio/video contents. Delay requirements are very strict in interactive real-time scenarios (such as synchronous distance learning), where playback lag should be of the order of seconds. Playback continuity is another key aspect in these cases: in presence of peer churning and network congestion, a peer-to-peer overlay should quickly rearrange connections among receiving nodes to avoid freezing phenomena that may compromise audio/video understanding. For this reason, we designed a QoS monitoring algorithm that quickly detects broken or congested links: each receiving node is able to independently decide whether it should switch to a secondary sending node, called "fallback node". The architecture takes advantage of a multithreaded design based on lock-free data structures, which improve the performance by avoiding synchronization among threads. We will show the good responsiveness of the proposed approach on machines with different computational capabilities: measured times prove both departures of nodes and QoS degradations are promptly detected and clients can quickly restore a stream reception. According to PSNR and SSIM, two well-known full-reference video quality metrics, QoE remains acceptable on receiving nodes of our resilient overlay also in presence of swap procedures.
机译:点对点流是一种众所周知的实时音频/视频内容的大规模分布技术。延迟要求非常严格,在交互式实时场景(如同步距离学习),播放滞后应该是秒的顺序。播放连续性是在这些情况下的另一个关键方面:在对等体搅拌和网络拥塞中,对等覆盖应该快速重新排列接收节点之间的连接,以避免可能损害音频/视频理解的冻结现象。因此,我们设计了一种快速检测破坏或拥塞链接的QoS监控算法:每个接收节点能够独立地决定它是否应该切换到辅助发送节点,称为“回退节点”。该架构利用基于无锁定数据结构的多线程设计,通过避免线程之间的同步来提高性能。我们将在具有不同计算能力的机器上展示所提出的方法的良好响应性:测量时间证明了每个节点的偏离,并迅速检测到QoS降级,并且客户可以快速恢复流接收。根据PSNR和SSIM,两个众所周知的全参考视频质量指标,QoE在存在换档程序的情况下,QoE也在接收我们的弹性覆盖层的节点上。

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