论文标题
降低多类处理网络的模拟差异
Variance Reduction in Simulation of Multiclass Processing Networks
论文作者
论文摘要
我们使用仿真来估计稳定的多类排队网络的稳态性能。当网络大量加载时，已经看到标准估计器的性能很差。我们介绍了两个新的仿真估计器。第一个以很少的额外计算成本提供了中等加载网络的大幅差异。第二个估计器可降低流量的大幅度差异，再次获得较小的额外计算成本。两种方法都采用了降低控制变体的方差方法，并且在控制变体的构建方式方面有所不同。
We use simulation to estimate the steady-state performance of a stable multiclass queueing network. Standard estimators have been seen to perform poorly when the network is heavily loaded. We introduce two new simulation estimators. The first provides substantial variance reductions in moderately-loaded networks at very little additional computational cost. The second estimator provides substantial variance reductions in heavy traffic, again for a small additional computational cost. Both methods employ the variance reduction method of control variates, and differ in terms of how the control variates are constructed.
