Importance sampling for the estimation of buffer overflow probabilities via trace-driven simulations
Importance sampling for the estimation of buffer overflow probabilities via trace-driven simulations
复制标题
通过跟踪驱动模拟来估计缓冲区溢出概率的重要性采样
DOI：
10.1109/tnet.2004.836139
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
S. Vassilaras
中科院分区：
文献类型：
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作者：
I. Paschalidis;S. Vassilaras
我们开发了一种重要的采样技术，可用于加快仿真的缓冲通信多路复用器的模型，由大量的独立的来源。源根据具有随机相位的周期函数生成业务。该业务模型适应了广泛的实际感兴趣的情况，包括ON-OFF周期性业务模型和由实际可变比特率源（例如MPEG视频压缩器）生成的比特率序列。该模拟试图获得缓冲区溢出概率的估计，在大多数情况下，感兴趣的是非常小的。我们使用一个大的偏差的结果来设计的重要性抽样技术中使用的措施的变化，并通过数值结果表明，这种变化的措施导致所需的模拟时间大大减少直接蒙特卡罗模拟。可能的实际应用包括短期网络资源规划，甚至实时呼叫准入控制。
We develop an importance sampling technique that can be used to speed up the simulation of a model of a buffered communication multiplexer fed by a large number of independent sources. The sources generate traffic according to a periodic function with a random phase. This traffic model accommodates a wide range of situations of practical interest, including ON-OFF periodic traffic models and sequences of bit rates generated by actual variable bit rate sources, such as MPEG video compressors. The simulation seeks to obtain estimates for the buffer overflow probability that in most cases of interest is very small. We use a large deviations result to devise the change of measure used in the importance sampling technique and demonstrate through numerical results that this change of measure leads to a dramatic reduction in the required simulation time over direct Monte Carlo simulation. Possible practical applications include short-term network resource planning and even real-time call admission control.