Variance Reduction in Simulation of Multiclass Processing Networks
نویسندگان
چکیده
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. ∗Work supported in part by NSF grant DMI-0224884 †Work supported in part by NSF grants DMI-0224884 and ECS 940372
منابع مشابه
Variance Reduction in Simulation of Multiclass Queueing Networks
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 substan...
متن کاملPerformance Evaluation and Policy Selection in Multiclass Networks
This paper concerns modelling and policy synthesis for regulation of multiclass queueing networks. A 2-parameter network model is introduced to allow independent modelling of variability and mean processing-rates, while maintaining simplicity of the model. Policy synthesis is based on consideration of more tractable workload models, and then translating a policy from this abstraction to the dis...
متن کاملModeling Structural Relationships of Meta-Cognitive Situations with Tendency to Virtual Networks through Mediating of Emotional Processing in Gifted Students
Background: Cyberspace covers many aspects of human life and tendency to cyberspace can be influenced by cognitive and emotional dimensions. Thus, the aim of this study was modeling structural relationships of meta-cognitive situations with tendency for virtual networks through mediating emotional processing in gifted students. Methods: The research method was descriptive-correlation and in pa...
متن کاملA hybrid EEG-based emotion recognition approach using Wavelet Convolutional Neural Networks (WCNN) and support vector machine
Nowadays, deep learning and convolutional neural networks (CNNs) have become widespread tools in many biomedical engineering studies. CNN is an end-to-end tool which makes processing procedure integrated, but in some situations, this processing tool requires to be fused with machine learning methods to be more accurate. In this paper, a hybrid approach based on deep features extracted from Wave...
متن کاملPlanar and SPECT Monte Carlo acceleration using a variance reduction technique in I131 imaging
Background: Various variance reduction techniques such as forced detection (FD) have been implemented in Monte Carlo (MC) simulation of nuclear medicine in an effort to decrease the simulation time while keeping accuracy. However most of these techniques still result in very long MC simulation times for being implemented into routine use. Materials and Methods: Convolution-based force...
متن کامل