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物联网下影响网络丢包的长相关性的因素对丢包率的影响
The Influencing Factors of Network Packet Loss’s Long-Range Dependence Have Impacts on the Packet Loss Rate under the Internet of Things

DOI: 10.12677/SEA.2019.83015, PP. 121-130

Keywords: 无参考,质量评估模型,网络丢包,长相关性丢包,网络丢包的长相关性
No-Reference
, Quality Assessment Model, Network Packet Loss, Long-Range Dependence, The Long Phase of Network Packet Loss

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Abstract:

物联网和网络视频丢包率到用户体验质量的映射模型是学术界和工商界的热点话题。为了更好地建立考虑网络丢包的视频质量无参评估模型得到更好的QoE评价,通过建立cygwin + NS2的网络环境对网络中丢包的尺度特性进行研究,丢包的尺度特性通过影响丢包率来影响QoE。实验结果表明,丢包的过程具有长相关性,叠加源个数N,形状参数和Hurst参数以及输出链路速度都可以影响丢包的长相关性。得出的结论是叠加源个数越多,形状参数越小,Hurst参数越大,输出链路速度越小,则丢包的长相关性越大,丢包率越大。
The mapping model of the network and network video packet loss rate to the quality of user experi-ence is a hot topic in the academia and the industry and commerce. In order to better establish no-reference video quality assessment model considering the network packet loss and further gain a better QoE evaluation, so we build NS2 + MyEvalvid simulation platform to study the scale characteristic of the network packet loss, scale characteristic of packet loss through the influence of packet loss rate to influence QoE. The experimental results show that packet loss processes have long-range dependence, and the number of superimposed source N, shape parameter, Hurst parameter and the output link speed have impacts on long-range dependence. We came to the conclusion that when superimposed source N is more, shape parameter is smaller, Hurst parameter is bigger, the output link speed is smaller, packet loss’s long range dependence is larger, packet loss rate is high.

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