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On optimization of continuous-time Markov networks in distributed computing

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Abstract

The paper presents a new stochastic model for studying the optimization of functioning rules in distributed computing. In this model a network is represented by a finite number of continuous-time homogeneous Markov processes which are connected by relations between entries of their intensity matrices. Good functioning rules are those optimizing a guide function defined according to the context. Two specific optimization problems are studied: a problem of resource allocation with conflicts between processes, and a problem of access to shared resources. The latter is a linearly constrained nonconvex problem with an objective function which is a sum of ratios of linear functions of special form.

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Authors and Affiliations

  1. LaRIA, Université de Picardie Jules Verne, France

    Alain Bui

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  1. Alain Bui
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Bui, A. On optimization of continuous-time Markov networks in distributed computing. Journal of Global Optimization 15, 299–314 (1999). https://doi.org/10.1023/A:1008328915992

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  • DOI: https://doi.org/10.1023/A:1008328915992

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