<mets:mets OBJID="eprint_13247" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2022-03-19T16:10:38Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Zhytomyr State University Library</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_13247_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>Stationary probability distribution of a system with N equal&#13;
customers with bursty demands connected to a single buffer</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">R. D.</mods:namePart><mods:namePart type="family">Rodríguez-Saіd</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">А. А.</mods:namePart><mods:namePart type="family">Pogoruі</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">Ramón М.</mods:namePart><mods:namePart type="family">Rodríguez-Dagnіno</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>In this paper we study the stationary probability distribution of a system consisting of a finite capacity buffer connected to N equal customers with bursty on-off demands. We assume that the buffer is filled up at a constant rate and we analyze the case when this filling rate satisfies an optimization condition according to the customer demands. First, we consider semi-Markov on-off demands for the case N = 2 and we model the dynamics of the system using a semi-Markov evolution environment. We show that we can use the phase merging algorithm to reduce the problem to a Markov evolution environment case. Then, we generalize the results for any N using a birth-and-death process.</mods:abstract><mods:classification authority="lcc">Mathematical Analysis</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2007</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>ROSE</mods:publisher></mods:originInfo><mods:genre>Article</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_13247"><mets:rightsMD ID="rights_eprint_13247_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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