Development of radio admission scheme model for 5G network slicing framework as a retrial queue F. Moskaleva, E. Y. Lisovskaya, L. Lapshenkova [et al.]
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ArticleContent type: Текст Media type: электронный Subject(s): очереди повторных попыток | нарезка сети | математические модели | метод асимптотического анализа | 5G-сети мобильныеGenre/Form: статьи в сборниках Online resources: Click here to access online
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Распределенные компьютерные и телекоммуникационные сети: управление, вычисление, связь DCCN-2021 [Электронный ресурс] : материалы XXIV Международной научной конференции (20-24 сентября 2021 г., Москва, Россия) С. 409-414Abstract: To improve the efficiency of using network resources, fifth-generation 5G networks propose to use the technology of network slicing. This feature consists of creating multiple logical, self-contained networks on top of a common shared physical infrastructure, and, therefore, it can be used to support multi-tenancy on the 5G network. Each of these logical networks is referred to as a network slice and can be tailored to provide a particular system behavior to best support specific service/application domains. This work is devoted to the development of a mathematical model of resource allocation in network slicing. Using the firstorder asymptotic analysis method, we will find basic numerical and probabilistic characteristics.
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To improve the efficiency of using network resources, fifth-generation 5G networks propose to use the technology of network slicing. This feature consists of creating multiple logical, self-contained networks on top of a common shared physical infrastructure, and, therefore, it can be used to support multi-tenancy on the 5G network. Each of these logical networks is referred to as a network slice and can be tailored to provide a particular system behavior to best support specific service/application domains. This work is devoted to the development of a mathematical model of resource allocation in network slicing. Using the firstorder asymptotic analysis method, we will find basic numerical and probabilistic characteristics.
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