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	    <datestamp>2025-07-22T13:33:44Z</datestamp>
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<dc:title xml:lang="pl"><![CDATA[A multi-source fluid queue based stochastic model of the probabilistic offloading strategy in a MEC system with multiple mobile devices and a single MEC server]]></dc:title>
<dc:creator><![CDATA[Zheng, Huan]]></dc:creator>
<dc:creator><![CDATA[Jin, Shunfu]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[mobile edge computing]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[probabilistic offloading strategy]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[multi-source fluid queue]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[birth-and-death process]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[cumulative distribution function]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[Mobile edge computing (MEC) is one of the key technologies to achieve high bandwidth, low latency and reliable service in fifth generation (5G) networks. In order to better evaluate the performance of the probabilistic offloading strategy in a MEC system, we give a modeling method to capture the stochastic behavior of tasks based on a multi-source fluid queue. Considering multiple mobile devices (MDs) in a MEC system, we build a multi-source fluid queue to model the tasks offloaded to the MEC server.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[We give an approach to analyze the fluid queue driven by multiple independent heterogeneous finite-state birth-and-death processes (BDPs) and present the cumulative distribution function (CDF) of the edge buffer content. Then, we evaluate the performance measures in terms of the utilization of the MEC server, the expected edge buffer content and the average response time of a task. Finally, we provide numerical results with some analysis to illustrate the feasibility of the stochastic model built in this paper.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Korbicz, Józef (1951- ) - red.]]></dc:contributor>
<dc:contributor><![CDATA[Uciński, Dariusz - red.]]></dc:contributor>
<dc:date><![CDATA[2022]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/86376/AMCS_2022_32_1_10.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/101449/edition/86376/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:86376]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 32, number 1 (2022)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=123]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:101449]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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