An infinite server system with packing constraints and ranked servers

Abstract A service system with multiple types of customers, arriving as Poisson processes, is considered. The system has infinite number of servers, ranked by $$1,2,3, \ldots $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mn>3</mml:mn> <mml:mo>,</mml:mo> <mml:mo>…</mml:mo> </mml:mrow> </mml:math> ; a server rank is its “location." Each customer has an independent exponentially distributed service time, with the mean determined by its type. Multiple customers (possibly of different types) can be placed for service into one server, subject to “packing” constraints. Service times of different customers are independent, even if served simultaneously by the same server. The large-scale asymptotic regime is considered, such that the mean number of customers r goes to infinity. We seek algorithms with the underlying objective of minimizing the location (rank) U of the right-most (highest ranked) occupied (non-empty) server. Therefore, this objective seeks to minimize the total number Q of occupied servers and keep the set of occupied servers as far at the “left” as possible, i.e., keep U close to Q . In previous work, versions of Greedy Random (GRAND) algorithm have been shown to asymptotically minimize Q / r as $$r\rightarrow \infty $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>r</mml:mi> <mml:mo>→</mml:mo> <mml:mi>∞</mml:mi> </mml:mrow> </mml:math> . In this paper, we show that when these algorithms are combined with the First-Fit rule for “taking” empty servers, they asymptotically minimize U / r as well.

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Publication Details

Journal
Queueing Systems
Published
2025-06-22
DOI
https://doi.org/10.1007/s11134-025-09945-2
Primary Topic
Advanced Queuing Theory Analysis
Type
article
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article

An infinite server system with packing constraints and ranked servers

Alexander Stolyar
Queueing Systems
Advanced Queuing Theory Analysis
article

An infinite server system with packing constraints and ranked servers

Alexander Stolyar
article en

Abstract

Abstract A service system with multiple types of customers, arriving as Poisson processes, is considered. The system has infinite number of servers, ranked by $$1,2,3, \ldots $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mn>3</mml:mn> <mml:mo>,</mml:mo> <mml:mo>…</mml:mo> </mml:mrow> </mml:math> ; a server rank is its “location." Each customer has an independent exponentially distributed service time, with the mean determined by its type. Multiple customers (possibly of different types) can be placed for service into one server, subject to “packing” constraints. Service times of different customers are independent, even if served simultaneously by the same server. The large-scale asymptotic regime is considered, such that the mean number of customers r goes to infinity. We seek algorithms with the underlying objective of minimizing the location (rank) U of the right-most (highest ranked) occupied (non-empty) server. Therefore, this objective seeks to minimize the total number Q of occupied servers and keep the set of occupied servers as far at the “left” as possible, i.e., keep U close to Q . In previous work, versions of Greedy Random (GRAND) algorithm have been shown to asymptotically minimize Q / r as $$r\rightarrow \infty $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>r</mml:mi> <mml:mo>→</mml:mo> <mml:mi>∞</mml:mi> </mml:mrow> </mml:math> . In this paper, we show that when these algorithms are combined with the First-Fit rule for “taking” empty servers, they asymptotically minimize U / r as well.

Queueing SystemsVol. 109(3)
University of Illinois Urbana-Champaign (US)
Openalex Percentile: Top 75%
Advanced Queuing Theory Analysis
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An infinite server system with packing constraints and ranked servers — Alexander Stolyar · Queueing Systems (2025) | TGRS Research Map | TGRS