Functional central limit theorems for Markov-modulated infinite-server systems
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In this paper we study the Markov-modulated M/M/\(\infty \) queue, with a focus on the correlation structure of the number of jobs in the system. The main results describe the system’s asymptotic behavior under a particular scaling of the model parameters in terms of a functional central limit theorem. More specifically, relying on the martingale central limit theorem, this result is established, covering the situation in which the arrival rates are sped up by a factor N and the transition rates of the background process by \(N^\alpha \), for some \(\alpha >0\). The results reveal an interesting dichotomy, with crucially different behavior for \(\alpha >1\) and \(\alpha <1\), respectively. The limiting Gaussian process, which is of the Ornstein–Uhlenbeck type, is explicitly identified, and it is shown to be in accordance with explicit results on the mean, variances and covariances of the number of jobs in the system.
KeywordsQueues Infinite-server systems Markov modulation Central limit theorems
The authors thank Peter Spreij (Korteweg-de Vries Institute for Mathematics, University of Amsterdam) for useful suggestions.
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