Multiserver-job response time under multilevel scaling

We study the multiserver-job setting in the load-focused multilevel scaling limit, where system load approaches capacity much faster than the growth of the number of servers $n$ . We consider the “1 and $n$ ” system, where each job requires either one server or all $n$ . Within the multilevel scaling limit, we examine three regimes: load dominated by $n$ -server jobs, 1-server jobs, or balanced. In each regime, we characterize the asymptotic growth rate of the boundary of the stability region and the scaled mean queue length. We demonstrate that mean queue length peaks near balanced load via theory, numerics, and simulation.

Publication Details

Journal
Probability in the Engineering and Informational Sciences
Published
2026-03-27
DOI
https://doi.org/10.1017/s0269964826100266
Primary Topic
Advanced Queuing Theory Analysis
Type
article
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article

Multiserver-job response time under multilevel scaling

Probability in the Engineering and Informational Sciences
Advanced Queuing Theory Analysis
article

Multiserver-job response time under multilevel scaling

article en

Abstract

We study the multiserver-job setting in the load-focused multilevel scaling limit, where system load approaches capacity much faster than the growth of the number of servers $n$ . We consider the “1 and $n$ ” system, where each job requires either one server or all $n$ . Within the multilevel scaling limit, we examine three regimes: load dominated by $n$ -server jobs, 1-server jobs, or balanced. In each regime, we characterize the asymptotic growth rate of the boundary of the stability region and the scaled mean queue length. We demonstrate that mean queue length peaks near balanced load via theory, numerics, and simulation.

Probability in the Engineering and Informational Sciences
Decent work and economic growth
Openalex Percentile: Top 4%
Advanced Queuing Theory Analysis
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Multiserver-job response time under multilevel scaling · Probability in the Engineering and Informational Sciences (2026) | TGRS Research Map | TGRS