A Restless Time-Fractional Multiclass Queue

Abstract We study a single-server priority queue with a finite number of classes, in which the arrivals follow a fractional Poisson process of index $$\alpha \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> and the service completions are triggered by an independent fractional Poisson process of index $$\beta \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>β</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> . Each of the customers arriving is assigned at random to one of the priority classes. This assignment is independent of the rest of the system and follows a fixed probability distribution. Using a time-change representation of a fractional Poisson process, we first give a multinomial thinning decomposition: The total number of arrivals in each class are independent standard Poisson processes of appropriate intensities, time-changed by a common independent random clock that is the inverse of an $$\alpha $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -stable subordinator. This yields a process-level law of large numbers and a functional central limit theorem for the process of arrivals. For the queueing system itself, we identify process-level scaling limits for the cumulative and individual queue lengths of the classes. We also prove that the queue gets empty infinitely often when $$\alpha \le \beta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>β</mml:mi> </mml:mrow> </mml:math> , which does include the critical case $$\alpha = \beta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>=</mml:mo> <mml:mi>β</mml:mi> </mml:mrow> </mml:math> . A final example shows how the model can be extended to a continuum of classes.

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Journal
Journal of Theoretical Probability
Published
2026-03-27
DOI
https://doi.org/10.1007/s10959-026-01494-5
Primary Topic
Advanced Queuing Theory Analysis
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article
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article

A Restless Time-Fractional Multiclass Queue

Enrico Scalas, Nicos Georgiou, Vladislav Vysotsky
Journal of Theoretical Probability
Advanced Queuing Theory Analysis
article

A Restless Time-Fractional Multiclass Queue

Enrico Scalas, Nicos Georgiou, Vladislav Vysotsky
article en

Abstract

Abstract We study a single-server priority queue with a finite number of classes, in which the arrivals follow a fractional Poisson process of index $$\alpha \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> and the service completions are triggered by an independent fractional Poisson process of index $$\beta \in (0,1]$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>β</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>(</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>]</mml:mo> </mml:mrow> </mml:math> . Each of the customers arriving is assigned at random to one of the priority classes. This assignment is independent of the rest of the system and follows a fixed probability distribution. Using a time-change representation of a fractional Poisson process, we first give a multinomial thinning decomposition: The total number of arrivals in each class are independent standard Poisson processes of appropriate intensities, time-changed by a common independent random clock that is the inverse of an $$\alpha $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>α</mml:mi> </mml:math> -stable subordinator. This yields a process-level law of large numbers and a functional central limit theorem for the process of arrivals. For the queueing system itself, we identify process-level scaling limits for the cumulative and individual queue lengths of the classes. We also prove that the queue gets empty infinitely often when $$\alpha \le \beta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>β</mml:mi> </mml:mrow> </mml:math> , which does include the critical case $$\alpha = \beta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>α</mml:mi> <mml:mo>=</mml:mo> <mml:mi>β</mml:mi> </mml:mrow> </mml:math> . A final example shows how the model can be extended to a continuum of classes.

Journal of Theoretical ProbabilityVol. 39(2)
University of Sussex (GB), Sapienza University of Rome (IT)
Openalex Percentile: Top 4%
Advanced Queuing Theory Analysis
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