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

A parallel server system is a stochastic processing network with applicationsin manufacturing, supply chain, ride-hailing, call centers, etc. Heterogeneouscustomers arrive in the system, and only a subset of servers can serve anycustomer type given by the flexibility graph. The goal of the system operatoris to minimize the delay that depends on the scheduling policy and theflexibility graph. A long line of literature focuses on designing near-optimalscheduling policies given a flexibility graph. On the contrary, we fix thescheduling policy to be the so-called MaxWeight scheduling given its superiordelay performance and focus on designing near-optimal, sparse flexibilitygraphs. Our contributions are threefold.  First, we analyze the expected delay in the heavy-traffic asymptotic regimein terms of the properties of the flexibility graph and use this result totranslate the design question in terms of transportation polytope, thedeterministic equivalent of parallel server queues. Second, we design thesparsest flexibility graph that achieves a given delay performance and showsthe robustness of the design to demand uncertainty. Third, given the budget toadd edges arrives sequentially in time, we present the optimal schedule foradding them to the flexibility graph. These results are obtained by proving newresults for transportation polytopes and are of independent interest. Inparticular, translating the difficulties to a simpler model, i.e.transportation polytope, allows us to develop a unified framework to answerseveral design questions.

Transportation Polytope and its Applications in Parallel Server Systems