Asset Details
Do you wish to reserve the book?
Economies-of-Scale in Many-Server Queueing Systems: Tutorial and Partial Review of the QED Halfin-Whitt Heavy-Traffic Regime
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Economies-of-Scale in Many-Server Queueing Systems: Tutorial and Partial Review of the QED Halfin-Whitt Heavy-Traffic Regime
Do you wish to request the book?
Economies-of-Scale in Many-Server Queueing Systems: Tutorial and Partial Review of the QED Halfin-Whitt Heavy-Traffic Regime
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Economies-of-Scale in Many-Server Queueing Systems: Tutorial and Partial Review of the QED Halfin-Whitt Heavy-Traffic Regime
2019
Overview
Multiserver queueing systems describe situations in which users require service from multiple parallel servers. Examples include check-in lines at airports, waiting rooms in hospitals, queues in contact centers, data buffers in wireless networks, and delayed service in cloud data centers. These are all situations with jobs (clients, patients, tasks) and servers (agents, beds, processors) that have large capacity levels, ranging from the order of tens (checkouts) to thousands (processors). This survey investigates how to design such systems to exploit resource pooling and economies-of-scale. In particular, we review the mathematics behind the quality- and efficiency-driven (QED) regime, which lets the system operate close to full utilization, while the number of servers grows simultaneously large and delays remain manageable. Aimed at a broad audience, we describe in detail the mathematical concepts for the basic Markovian many-server system, and we provide only sketches or references for more advanced settings related to, e.g., load balancing, overdispersion, parameter uncertainty, general service requirements, and queueing networks. While serving as a partial survey of a massive body of work, the tutorial is not meant to be exhaustive.
Publisher
Society for Industrial and Applied Mathematics
Subject
