Packet scheduling based on Geo/sup Y//G//spl infin/ input process modeling for streaming video

Sujeong Choi, S. Kang, Bara Kim
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引用次数: 1

Abstract

We introduce a new stochastic process called Geo/sup Y//G//spl infin/ input process with beta-distributed batch size and Weibull-like autocorrelation function in order to model video traffic. Investigating the overflow probability of a queueing system by large deviation theory, we develop a streaming scheduling algorithm by applying the overflow analysis result to estimating the packet deadline-missing probability. Through experiments with 30-minute long movie traces, we show that our proposed scheduling scheme outperforms existing schemes based on fractional Brownian motion and Markovian models.
基于Geo/sup / Y/ G//spl infin/ input过程建模的流视频分组调度
为了对视频流量进行建模,我们引入了一种新的随机过程,称为Geo/sup / Y//G//spl / infin/ input过程,该过程具有beta分布批大小和类威布尔自相关函数。利用大偏差理论研究了排队系统的溢出概率,提出了一种基于溢出分析结果的流调度算法。通过30分钟长的电影轨迹实验,我们表明我们提出的调度方案优于现有的基于分数布朗运动和马尔可夫模型的调度方案。
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