Анализ методов идентификации трафика для управления ресурсами в SDN

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Статья посвящена анализу методов классификации трафика в сети SDN. Выполнен обзор аналитических подходов идентификации трафика для выявления применяемых в них решений, а также оценки их применимости в сети SDN. Рассмотрены виды машинного обучения и выполнен анализ входных параметров. Методы интеллектуального анализа, освещенные в научных статьях, систематизированы по следующим критериям: параметры идентификации трафика, модель нейронной сети, точность идентификации. На основании анализа результатов обзора сделан вывод о возможности применения рассмотренных решений, а также о необходимости формирования схемы сети SDN с модулем элементов искусственного интеллекта для балансировки нагрузки.

Об авторах

Ю. С. Дмитриева

Санкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-Бруевича

Email: dmitrieva@sut.ru
ORCID iD: 0000-0002-7736-7121

Д. В. Окунева

Санкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-Бруевича

Email: okuneva.dv@sut.ru
ORCID iD: 0009-0005-4241-8784

В. С. Елагин

Санкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-Бруевича

Email: v.elagin@sut.ru
ORCID iD: 0000-0003-4077-6869

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