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2021 | OriginalPaper | Buchkapitel

State Estimation in Partially Observed Stochastic Networks with Queueing Applications

verfasst von : Konstantin V. Semenikhin

Erschienen in: Modern Trends in Controlled Stochastic Processes:

Verlag: Springer International Publishing

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Abstract

The problem of filter-based state estimation for a partially observed stochastic network is considered in this paper, using the measure change approach. The network is assumed to have two types of nodes: observed and hidden. Their dynamics are defined by a set of counting processes with state-dependent intensities. The goal is to derive the nonlinear optimal filter and to propose a numerical scheme for its practical implementation. Network models that allow the optimal filter to be finite-dimensional are also considered. The theoretical results are applied to a retrial queuing system to track changes in two hidden stations: one accumulates blocked customers and the other contains unsatisfied customers.

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Metadaten
Titel
State Estimation in Partially Observed Stochastic Networks with Queueing Applications
verfasst von
Konstantin V. Semenikhin
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-76928-4_7