English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Multi-server queueing systems describe situations in which users requireservice from multiple parallel servers. Examples include check-in lines atairports, waiting rooms in hospitals, queues in contact centers, data buffersin wireless networks, and delayed service in cloud data centers. These are allsituations 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 designsuch 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 thenumber of servers grows simultaneously large and delays remain manageable.Aimed at a broad audience, we describe in detail the mathematical concepts forthe basic Markovian many-server system, and only provide sketches or referencesfor 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 isnot aimed to be exhaustive.

Economies-of-scale in resource sharing systems: tutorial and partial review of the QED heavy-traffic regime