IoT 15(3): e3

Research Article

Flow coupling and stochastic ordering of throughputs in linear networks

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  • @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
Lasse Leskelä1,*
  • 1: Aalto University
*Contact email: lasse.leskela@aalto.fi

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.