Efficient approximation of response time densities and quantiles in stochastic models
Efficient approximation of response time densities and quantiles in stochastic models
复制标题
随机模型中响应时间密度和分位数的有效近似
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
W. Knottenbelt
中科院分区：
文献类型：
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作者：
S. Au;N. Dingle;W. Knottenbelt
响应时间密度和分位数是重要的性能和服务质量指标，但它们的分析推导通常非常昂贵。本文提出了一种确定马尔可夫和半马尔可夫随机模型中近似响应时间密度的技术，该技术所需的计算量比基于精确拉普拉斯变换的技术少两个数量级。该方法计算所需响应时间的前四个矩，然后使用广义Lambda分布来获得相应密度的近似值。数值结果表明，在响应时间曲线的范围内，特别是对那些单峰的响应时间曲线，有很好的一致性。
Response time densities and quantiles are important performance and quality of service metrics, but their analytical derivation is, in general, very expensive. This paper presents a technique for determining approximate response time densities in Markov and semi-Markov stochastic models that requires two orders of magnitude less computation than exact Laplace transform-based techniques. The method computes the first four moments of the desired response time and then makes use of Generalised Lambda Distributions to obtain an approximation of the corresponding density. Numerical results show good agreement over a range of response time curves, particularly for those that are unimodal.