Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data

Author:

Wang Weikun1,Casale Giuliano1

Affiliation:

1. Imperial College London, UK

Abstract

We propose maximum likelihood (ML) estimators for service demands in closed queueing networks with load-independent and load-dependent stations. Our ML estimators are expressed in implicit form and require only to compute mean queue lengths and marginal queue length probabilities from an empirical dataset. Further, in the load-independent case, we provide an explicit approximate formula for the ML estimator together with confidence intervals.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A survey of parameter and state estimation in queues;Queueing Systems;2021-02

2. Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data;Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering;2016-03-12

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