Strong Embeddings for Transitory Queueing Models

• 成果类型: Article
• 署名作者: Chakraborty, Prakash; Honnappa, Harsha
• 署名单位: Purdue University System; Purdue University; Purdue University System; Purdue University
• 刊物名称: MATHEMATICS OF OPERATIONS RESEARCH
• ISSN/ISSBN: 0364-765X
• DOI: 10.1287/moor.2021.1158
• 发表日期: 2022
• 页码: 1048-1081
• 关键词: strong approximations; queues; arrival

摘要

In this paper, we establish strong embedding theorems, in the sense of the Komlos-Major-Tusnady 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 formof functional strong approximation theorems.