Strong Embeddings for Transitory Queueing Models

Prakash Chakraborty () and Harsha Honnappa ()
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Prakash Chakraborty: Department of Statistics, Purdue University, West Lafayette, Indiana 47906
Harsha Honnappa: School of Industrial Engineering, Purdue University, West Lafayette, Indiana 47906

Mathematics of Operations Research, 2022, vol. 47, issue 2, 1048-1081

Abstract: In this paper, we establish strong embedding theorems, in the sense of the Komlós-Major-Tusnády framework, for the performance metrics of a general class of transitory queueing models of nonstationary queueing systems. The nonstationary and non-Markovian nature of these models makes the computation of performance metrics hard. The strong embeddings yield error bounds on sample path approximations by diffusion processes in the form of functional strong approximation theorems.

Keywords: Primary: 60F17; 60K25; secondary: 90B22; nonstationary models; transitory models; strong approximations; queueing theory (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormoor:v:47:y:2022:i:2:p:1048-1081

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