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Exact tail asymptotics for fluid models driven by an M/M/c queue

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Abstract

In this paper, we investigate exact tail asymptotics for the stationary distribution of a fluid model driven by the M / M / c queue, which is a two-dimensional queueing system with a discrete phase and a continuous level. We extend the kernel method to study tail asymptotics of its stationary distribution, and a total of three types of exact tail asymptotics are identified from our study and reported in the paper.

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Acknowledgements

This research was supported in part by the National Natural Science Foundation of China (Grants 11571372, 11771452), Natural Science Foundation of Hunan (Grant Nos. 2018JJ4357, 2017JJ2328), and a Discovery Grant by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Appendix: Tauberian-like theorem

Appendix: Tauberian-like theorem

Denote

$$\begin{aligned} \varDelta _{1}(\phi , \varepsilon )=\left\{ x: |x|\le |x_{0}|+\varepsilon , |\arg (x-x_{0})|> \phi , \varepsilon >0, 0<\phi <\frac{\pi }{2}\right\} . \end{aligned}$$

Let \(f_{n}\) be a sequence of numbers with the generating function

$$\begin{aligned} f(x)=\sum _{n\ge 1} f_{n} x^{n}. \end{aligned}$$

Lemma 16

(Flajolet and Odlyzko 1990) Assume that f(x) is analytic in \(\varDelta _{1}(\phi , \varepsilon )\) except at \(x=x_{0}\) and

$$\begin{aligned} f(x)\sim K(x_{0}-x)^{s} \ \ \text{ as }\ \ x\rightarrow x_{0} \ \ \text{ in } \ \ \varDelta _{1}(\phi , \varepsilon ). \end{aligned}$$

Then, as \(n\rightarrow \infty \), (i) If \(s \not \in \{0, 1, 2, \ldots \}\),

$$\begin{aligned} f_{n}=\frac{K }{\varGamma (-s)}n^{-s-1}x_{0}^{-n}, \end{aligned}$$

where \(\varGamma (\cdot )\) is the Gamma function.

(ii) If s is a non-negative integer, then

$$\begin{aligned} f_{n}= o(n^{-s-1}x_{0}^{-n}). \end{aligned}$$

For the continuous case, let

$$\begin{aligned} g(x)=\int _{0}^{\infty }e^{xt}f(t)\mathrm{d}t. \end{aligned}$$

Denote

$$\begin{aligned} \varDelta _{2}(\phi , \varepsilon )=\{x: \mathfrak {R}(x)\le |x_{0}|+\varepsilon , x\ne x_{0}, \varepsilon>0, |\arg (x-x_{0})|> \phi \}. \end{aligned}$$

The following lemma is shown in Theorem 2 in [4].

Lemma 17

Assume that g(x) satisfies the following conditions:

  1. (i)

    The leftmost singularity of g(x) is \(x_{0}\), with \(x_{0} > 0\). Furthermore, we assume that as \(x\rightarrow x_{0}\),

    $$\begin{aligned} g(x)\sim (x_{0}-x)^{-s} \end{aligned}$$

    for some \(s\in \mathbb {C}\backslash Z_{-}\).

  2. (ii)

    g(x) is analytic on \(\varDelta _{2}(\phi _{0}, \varepsilon )\) for some \(\phi _{0}\in (0, \frac{\pi }{2}]\).

  3. (iii)

    g(x) is bounded on \(\varDelta _{2}(\phi _{1}, \varepsilon )\) for some \(\phi _{1}> 0\).

Then, as \(t\rightarrow \infty \),

$$\begin{aligned} f(t)\sim e^{-x_{0} t} \frac{t^{s-1}}{\varGamma (s)}, \end{aligned}$$

where \(\varGamma (\cdot )\) is the Gamma function.

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Li, W., Liu, Y. & Zhao, Y.Q. Exact tail asymptotics for fluid models driven by an M/M/c queue. Queueing Syst 91, 319–346 (2019). https://doi.org/10.1007/s11134-019-09601-6

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