Spectral Analysis and Asymptotic Behavior of an M/GB/1 Bulk Service Queueing System

In this paper, we investigate the spectrum distribution and asymptotic behavior of an M/GB/1 bulk service queueing system. In this system, the server processes customers in batches of a fixed maximum capacity B, and the time required to serve a batch is governed by a general distribution with a service rate function η(·), which determines the instantaneous probability of service completion. The system dynamics are described by an infinite set of partial integro-differential equations. First, by introducing the probability generating function and employing Greiner’s boundary perturbation method, we establish that the time-dependent solution (TDS) of the system converges strongly to its steady-state solution (SSS) in the natural Banach state space. To this end, when the service rate η(·) is a bounded function, we prove that zero is an eigenvalue of both the system operator and its adjoint operator, with geometric multiplicity one. Moreover, we show that every point on the imaginary axis except zero belongs to the resolvent set of the system operator. Second, we analyze the spectrum of the system operator on the left real axis. When the service rate η(·) is constant and the fixed maximum capacity B equals 2, we apply Jury’s stability criterion for cubic equations to demonstrate that the system operator possesses an uncountably infinite number of eigenvalues located on the negative real axis. Additionally, we prove that an open interval near zero on the left real axis is not part of the point spectrum of the system operator. Consequently, these results imply that the semigroup generated by the system operator is not compact, eventually compact, quasi-compact, or essentially compact.

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Publication Details

Journal
Axioms
Published
2026-03-24
DOI
https://doi.org/10.3390/axioms15040243
Primary Topic
Advanced Queuing Theory Analysis
Type
article
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Spectral Analysis and Asymptotic Behavior of an M/GB/1 Bulk Service Queueing System

Axioms
Advanced Queuing Theory Analysis
article

Spectral Analysis and Asymptotic Behavior of an M/GB/1 Bulk Service Queueing System

article en

Abstract

In this paper, we investigate the spectrum distribution and asymptotic behavior of an M/GB/1 bulk service queueing system. In this system, the server processes customers in batches of a fixed maximum capacity B, and the time required to serve a batch is governed by a general distribution with a service rate function η(·), which determines the instantaneous probability of service completion. The system dynamics are described by an infinite set of partial integro-differential equations. First, by introducing the probability generating function and employing Greiner’s boundary perturbation method, we establish that the time-dependent solution (TDS) of the system converges strongly to its steady-state solution (SSS) in the natural Banach state space. To this end, when the service rate η(·) is a bounded function, we prove that zero is an eigenvalue of both the system operator and its adjoint operator, with geometric multiplicity one. Moreover, we show that every point on the imaginary axis except zero belongs to the resolvent set of the system operator. Second, we analyze the spectrum of the system operator on the left real axis. When the service rate η(·) is constant and the fixed maximum capacity B equals 2, we apply Jury’s stability criterion for cubic equations to demonstrate that the system operator possesses an uncountably infinite number of eigenvalues located on the negative real axis. Additionally, we prove that an open interval near zero on the left real axis is not part of the point spectrum of the system operator. Consequently, these results imply that the semigroup generated by the system operator is not compact, eventually compact, quasi-compact, or essentially compact.

AxiomsVol. 15(4)
Xinjiang University (CN)
Openalex Percentile: Top 7%
Advanced Queuing Theory Analysis
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Spectral Analysis and Asymptotic Behavior of an M/GB/1 Bulk Service Queueing System · Axioms (2026) | TGRS Research Map | TGRS