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A Performance Analysis of Adaptive Streaming Algorithms in 5G Vehicular Communications in Urban Scenarios

机译:城市场景下5G车载通信中自适应流算法的性能分析

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Adaptive streaming is a technique used in multimedia over computer networks where the source content is encoded to decide about which bit-rate segments to download, through algorithms. The contribution of this work is the investigation about which and why an adaptation algorithm can be running included as service, aiming to relax network congestion while improving the user experience at onboard entertainment services. The goals of this present paper are the multimedia service delivery analysis to improve its efficiency in 5G vehicular communications, also to evaluate the vehicular Internet-based video services traffic in urban scenarios with different vehicle densities, and still to perform the vehicle-communication simulations in the 5G network to estimate the metrics for the algorithm selection. In this proposal, the studied metrics are the number of playback interruptions, video quality, quality of transitions, average buffer level, average bit-rate and bit-rate switching frequency, throughput, unfairness, instability, and inefficiency. The results have shown PANDA as the best adaptive streaming algorithm to perform videos in vehicular communications in urban scenarios.
机译:自适应流传输是在计算机网络上的多媒体中使用的一种技术,其中对源内容进行编码,以通过算法决定要下载的比特率段。这项工作的贡献在于调查了哪些自适应算法以及为什么可以运行自适应算法作为服务,旨在缓解网络拥塞并改善车载娱乐服务的用户体验。本文的目标是进行多媒体服务交付分析,以提高其在5G车辆通信中的效率,还评估具有不同车辆密度的城市场景中基于车辆的互联网视频服务的流量,并仍在进行车辆通信仿真。 5G网络以估算用于算法选择的指标。在此建议中,研究的指标是回放中断的数量,视频质量,转换质量,平均缓冲区级别,平均比特率和比特率切换频率,吞吐量,不公平性,不稳定和效率低下。结果表明,PANDA是在城市场景下的车辆通信中执行视频的最佳自适应流算法。

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