Parameter Estimation of Mt/M/1/K Queueing Systems With Utilization Data

Parameter Estimation of Mt/M/1/K Queueing Systems With Utilization Data
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利用利用率数据对 Mt/M/1/K 排队系统进行参数估计

DOI:
10.1109/access.2019.2906796
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发表时间:
2019
期刊:
影响因子:
3.9
通讯作者:
T. Dohi
T. Dohi
中科院分区:
计算机科学3区
文献类型:
--
作者:
C. Li;H. Okamura;T. Dohi

文献摘要

相似文献

利用率数据被定义为由固定时间间隔中的忙碌时段的时间部分组成的时间序列数据,并且实际上用于表示服务器状况,诸如CPU利用率。通常,从利用率数据估计模型参数更具挑战性,因为我们不知道确切的作业到达时间和利用率数据的服务时间。在本文中,我们考虑一种方法来估计模型参数的利用率数据假设一些模型的假设。特别地,我们假设一个Mt/M/1/K排队系统,其工件到达服从非齐次泊松过程(NHPP),并提出了一种基于极大似然估计(MLE)的NHPP参数估计方法,通过期望最大化(EM)算法近似从利用数据。在数值实验中,我们生成了Mt/M/1/K系统的模拟使用数据,并研究了我们的方法的有效性。此外,我们使用真实的CPU利用率数据来展示性能评估。
Utilization data are defined as the time series data consisting of time fractions of busy periods in fixed time intervals and are practically used to represent server conditions, such as CPU utilization. In general, it is more challenging to estimate the model parameters from the utilization data since we do not know the exact job arrival time and the service time from the utilization data. In this paper, we consider an approach to estimate the model parameters from the utilization data by assuming a few model assumptions. In particular, we suppose an Mt/M/1/K queueing system whose job arrival follows a Non-homogeneous Poisson Process (NHPP) and propose a parameter estimation method for the NHPP approximately from the utilization data based on the maximum likelihood estimation (MLE) via the expectation maximization (EM) algorithm. In numerical experiments, we generate the simulated utilization data of an Mt/M/1/K queueing system and investigate the effectiveness of our method. Also, we use the real CPU utilization data to exhibit the performance evaluation.