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Deriving Performance Distribution of Queueing System by Maximum Entropy Principle

机译:通过最大熵原理导出排队系统的性能分布

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Assumptions on the distributions of customer inter-arrival time and severing time are the basis of queueing system analyzing. This paper demonstrates that these assumptions are actually not necessary if there are some known macro-indexes such as the capacity of system, mean number of customers in system, mean utilization of server. We are not concerned with the arrival time and severing time distributions. We go directly to the performance distributions. A queueing system is looked as a black box without any assumptions on arrival time and serving time distributions, maximum entropy models are developed to derive the performance distribution of queuing system with some empirically easy-to-get indexes of queueing systems. We perform a comparative analysis between the exact results and the maximum entropy results by chi-square fit goodness test. We demonstrate that the maximum entropy principle approach is accurate enough for practical purposes.
机译:对客户际际时间和切断时间分布的假设是排队系统分析的基础。本文展示了这些假设实际上不是必要的,如果存在一些已知的宏索引,例如系统的容量,系统中的客户的平均值,平均使用服务器的宏索引。我们不关心到达时间和断裂时间分布。我们直接进入性能分布。在抵达时间和服务时间分布时,队列系统被视为没有任何假设的黑匣子,开发了最大熵模型,以导出排队系统的绩效分布与排队系统的一些经验易于获得的索引。我们在Chi-Square拟合良好测试之间进行确切结果和最大熵结果之间进行比较分析。我们证明,最大熵原理方法对于实际目的而言足够准确。

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