计算效率高的计算机模拟系统：R程序包计算机
Computationally Efficient Simulation of Queues: The R Package queuecomputer
摘要：
大型的嵌入式系统网络模拟了重要的现实世界系统，如MapReduce集群、Web服务器、医院、呼叫中心和机场客运终端。为了精确地模拟这样的系统，我们必须从数据中推断出相关参数。不幸的是，对于许多神经网络来说，没有明确的方法从数据中进行参数推断。如果我们能够足够快地模拟数据，近似贝叶斯计算可以提供一种直接的方法来推断这种网络的参数。我们提出了一种计算效率高的方法，从一个非常一般的一组嵌入式网络与R包嵌入式计算机进行模拟。相对于流行的DES包simmer和simpy，观察到超过2个数量级的显着加速。我们复制这些包的输出以验证包。该包是模块化的，并与流行的R包dapr很好地集成。使用这两个软件包可以轻松构建具有串联、并行和分叉/连接拓扑的复杂网络。我们将通过两个示例展示如何使用此包：呼叫中心和机场航站楼。
英文摘要：
Large networks of queueing systems model important real-world systems such as MapReduce clusters, web-servers, hospitals, call centers and airport passenger terminals. To model such systems accurately, we must infer queueing parameters from data. Unfortunately, for many queueing networks there is no clear way to proceed with parameter inference from data. Approximate Bayesian computation could offer a straightforward way to infer parameters for such networks if we could simulate data quickly enough. We present a computationally efficient method for simulating from a very general set of queueing networks with the R package queuecomputer. Remarkable speedups of more than 2 orders of magnitude are observed relative to the popular DES packages simmer and simpy. We replicate output from these packages to validate the package. The package is modular and integrates well with the popular R package dplyr. Complex queueing networks with tandem, parallel and fork/join topologies can easily be built with these two packages together. We show how to use this package with two examples: a call center and an airport terminal.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
