Asymptotically optimal importance sampling for product-form queuing networks
Asymptotically optimal importance sampling for product-form queuing networks
复制标题
产品形式排队网络的渐近最优重要性采样
DOI：
10.1145/174153.174160
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发表时间：
1993
期刊：
影响因子：
--
通讯作者：
Jie Wang
中科院分区：
文献类型：
--
作者：
K. Ross;Jie Wang
蒙特卡洛集成在产品形式多类排队网络的归一化常数的整体表示中，这些网络与单服务器，固定速率站和至少一个无限服务器站关闭。让每个班级的人口转到无穷大，因此得出了渐进式 - 隔间分布，以估算归一化常数和利用的估计。在正常使用方案中，其中单人服务器站的渐近利用严格少于一个，独立的指数samphng对于估计归一化常数是渐近的最佳选择。在同一制度中，用于估算使用的渐近最佳采样DMTRLBUTION在单个服务器站之间是复杂的，并且取决于。在关键的使用方案中，单个服务器站的渐近UTLHZATLON等于1，截短的多乘正常采样是渐近的最佳选择，用于估计正常化常数。
Monte Carlo integration M apphed to the integral representation of the normalization constant for a famdy of product-form multiclass queuing networks These networks are closed with single-server, fixed-rate stations and at least one infinite-server station. Letting the population for each class go to infinity, the asymptotically optimal importance-samphng distributions are derived for estimates of the normalization constant and of the utilizations. In the normal-usage regime, in which the asymptotic utilizations at the single-server stations are strictly less than one, independent exponential samphng is asymptotically optimal for estimating the normalization constant. In the same regime, the asymptotically optimal sampling dmtrlbution for estimatmg utilization is complex and dependent across single-server stations. In the critical-usage regime, m which the asymptotic utlhzatlons at the single-server stations are equal to one, truncated multivarlate normal sampling is asymptotically optimal for estimating the normalization constant.