Research Article
Flow coupling and stochastic ordering of throughputs in linear networks
@ARTICLE{10.4108/icst.valuetools.2014.258210, author={Lasse Leskel\aa{}}, title={Flow coupling and stochastic ordering of throughputs in linear networks}, journal={EAI Endorsed Transactions on Internet of Things}, volume={1}, number={3}, publisher={EAI}, journal_a={IOT}, year={2015}, month={2}, keywords={flow coupling, non-markov coupling, strong order, stochastic comparison, stochastic domination, stochastic monotonicity}, doi={10.4108/icst.valuetools.2014.258210} }- Lasse Leskelä
Year: 2015
Flow coupling and stochastic ordering of throughputs in linear networks
IOT
EAI
DOI: 10.4108/icst.valuetools.2014.258210
Abstract
Robust estimates for the performance of complicated queueing networks can be obtained by showing that the number of jobs in the network is stochastically comparable to a simpler, analytically tractable reference network. Classical coupling results on stochastic ordering of network populations require strong monotonicity assumptions which are often violated in practice. However, in most real-world applications we care more about what goes through a network than what sits inside it. This paper describes a new approach for ordering flows instead of populations by augmenting network states with their associated flow counting processes and deriving Markov couplings of the augmented state-flow processes.
Copyright © 2015 Lasse Leskelä, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
