基于初始时延与卡顿概率的视频流缓冲阈值确定

Determination of Video Streaming Buffer Threshold Constrainted with Initial Delay and Hysteresis Probability

基于随机流体模型(stochastic fluid model,SFM)框架,提出一种新的IP网络动态视频流系统的SFM模型,分析视频流系统卡顿发生概率与初始缓冲时延之间关系,从而确定最优缓冲阈值的设置。首先推导视频流系统3个首达时(first passage times,FPTs)的Laplace-Stieltjes(LST)变换矩阵,在此基础上得到卡顿发生概率和初始缓冲时延高于给定容忍时间概率;基于此,给出最佳缓冲阈值的算法设计;最后利用数值结果验证解析结论。

This paper proposes a novel stochastic fluid model(SFM)framework to describe the IP network dynamic video streaming system.The goal is to weigh the relationship between the hysteresis probability and the initial buffer delay,and then to determine an optimal buffer threshold setting.Firstly,the Laplace-Stieltjes transform(LST)matrices of the three First Passage Times(FPTs)is derived in the video streaming system,and then the occurrence probability of the hysteresis is obtained as well as the probability that the initial buffer time is higher than the given tolerable time.Based on these results,the control optimization problem of the initial buffer threshold is further constructed,and an algorithm is designed to find the optimal buffer threshold.Finally,a numerical result is provided to confirm the theoretical findings.