论文标题

Qudash:dash视频流的量子风格的速率适应方法

QuDASH: Quantum-inspired rate adaptation approach for DASH video streaming

论文作者

Wei, Bo, Song, Hang, Nakamura, Makoto, Kimura, Koichi, Togawa, Nozomu, Katto, Jiro

论文摘要

随着网络技术的开发和视频流流量的开发,互联网流量大大增加,在总流量内大量占据了大量资金,这揭示了保证内容交付服务质量的重要性。根据网络条件,自适应比特率(ABR)控制被用作一种通用技术,可以选择合适的比特率以确保视频流质量。在本文中,通过利用新兴量子技术来提出新的比特率控制方法。在Qudash中,自适应控制模型是使用二次无约束二进制优化(QUBO)开发的,该模型旨在增加平均比特率并降低视频重新恢复事件,以最大程度地提高体验用户质量(QOE)。为了制定视频控制模型,首先定义了有关视频质量,比特率更改和缓冲条件的不同因素的QUBO项。然后,将所有单个Qubo项合并以生成目标函数。通过最小化QUBO目标函数,从解决方案中确定了比特率选择。控制模型由数字退火器解决,这是一种受量子启发的计算技术。通过模拟在不同场景下在现实世界中获得的吞吐量痕迹进行模拟进行评估,并进行了与其他方法的比较。实验结果表明,与其他高级ABR方法相比,提出的Qudash方法在QOE方面具有更好的性能。在68.2%的案例中,Qudash取得了最高的QOE结果,这表明了Qudash的优势,而不是常规方法。

Internet traffic is dramatically increasing with the development of network technologies and video streaming traffic accounts for large amount within the total traffic, which reveals the importance to guarantee the quality of content delivery service. Based on the network conditions, adaptive bitrate (ABR) control is utilized as a common technique which can choose the proper bitrate to ensure the video streaming quality. In this paper, new bitrate control method, QuDASH is proposed by taking advantage of the emerging quantum technology. In QuDASH, the adaptive control model is developed using the quadratic unconstrained binary optimization (QUBO), which aims at increasing the average bitrate and decreasing the video rebuffering events to maximize the user quality of experience (QoE). In order to formulate the video control model, first the QUBO terms of different factors are defined regarding video quality, bitrate change, and buffer condition. Then, all the individual QUBO terms are merged to generate an objective function. By minimizing the QUBO objective function, the bitrate choice is determined from the solution. The control model is solved by Digital Annealer, which is a quantum-inspired computing technology. The evaluation of the proposed method is carried out by simulation with the throughput traces obtained in real world under different scenarios and the comparison with other methods is conducted. Experiment results demonstrated that the proposed QuDASH method has better performance in terms of QoE compared with other advanced ABR methods. In 68.2% of the examined cases, QuDASH achieves the highest QoE results, which shows the superiority of the QuDASH over conventional methods.

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