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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">tuzsut</journal-id><journal-title-group><journal-title xml:lang="ru">Труды учебных заведений связи</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of Telecommunication Universities</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1813-324X</issn><issn pub-type="epub">2712-8830</issn><publisher><publisher-name>СПбГУТ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.31854/1813-324X-2026-12-4-37-52</article-id><article-id custom-type="edn" pub-id-type="custom">LRQMPY</article-id><article-id custom-type="elpub" pub-id-type="custom">tuzsut-824</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>КОМПЬЮТЕРНЫЕ НАУКИ И ИНФОРМАТИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>COMPUTER SCIENCE AND INFORMATICS</subject></subj-group></article-categories><title-group><article-title>Анализ микросервисных подходов к V2X-системам с периферийными вычислениями</article-title><trans-title-group xml:lang="en"><trans-title>Analysis of Microservice Approaches to V2X Systems with Edge Computing</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0006-8034-0516</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Тамбовцев</surname><given-names>Г. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Tambovtsev</surname><given-names>G. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант, ассистент кафедры высшей математики Санкт-Петербургского государственного университета телекоммуникаций им. проф. М.А. Бонч-Бруевича</p></bio><email xlink:type="simple">tambovcev.gi@sut.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8852-5607</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Владыко</surname><given-names>А. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Vladyko</surname><given-names>A. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат технических наук, доцент, декан факультета радиоэлектронных систем и робототехники Санкт-Петербургского государственного университета телекоммуникаций им. проф. М.А. Бонч-Бруевича</p></bio><email xlink:type="simple">vladyko@sut.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8869-6142</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Плотников</surname><given-names>П. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Plotnikov</surname><given-names>P. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат физико-математических наук, доцент, заведующий кафедрой высшей математики Санкт-Петербургского государственного университета телекоммуникаций им. проф. М.А. Бонч-Бруевича</p></bio><email xlink:type="simple">plotnikov.pv@sut.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Санкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-Бруевича</institution><country>Россия</country></aff><aff xml:lang="en"><institution>The Bonch-Bruevich Saint Petersburg State University of Telecommunications</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>31</day><month>08</month><year>2026</year></pub-date><volume>12</volume><issue>4</issue><fpage>37</fpage><lpage>52</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Тамбовцев Г.И., Владыко А.Г., Плотников П.В., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Тамбовцев Г.И., Владыко А.Г., Плотников П.В.</copyright-holder><copyright-holder xml:lang="en">Tambovtsev G.I., Vladyko A.G., Plotnikov P.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://tuzs.sut.ru/jour/article/view/824">https://tuzs.sut.ru/jour/article/view/824</self-uri><abstract><sec><title>Актуальность</title><p>Актуальность. Развитие V2X-систем и перенос вычислений на периферийные и туманные узлы требуют применения средств контейнеризации и оркестрации, однако их собственные накладные расходы могут снижать эффект от распределения сервисов и особенно значимы для ресурсно-ограниченной инфраструктуры. </p><p>Цель исследования – оценить ресурсную стоимость применения KubeEdge поверх K3s при одинаковой микросервисной нагрузке, имитирующей обработку V2X-сообщений, и сформировать базовый уровень для последующей оценки прикладных алгоритмов размещения сервисов. </p></sec><sec><title>Методы</title><p>Методы. Выполнены обзор и систематизация современных микросервисных подходов к V2X, edge- и fog-вычислениям. Экспериментально сопоставлены конфигурации K3s и K3s + KubeEdge на одной облачной VPS при неизменных аппаратных ресурсах, программном окружении и пяти профилях нагрузки от idle до stress. Каждый профиль выполнялся три раза, после чего результаты усреднялись. Измерялись загрузка CPU, потребление оперативной памяти, сетевой трафик, число запросов и 95-й и 99-й перцентили задержки. </p></sec><sec><title>Результаты</title><p>Результаты. Добавление KubeEdge увеличило потребление оперативной памяти примерно на 95–105 МБ, или 6–8 % относительно K3s. Различия по CPU, сетевому трафику и задержкам оказались незначительными; рост p95/p99 при высокой нагрузке наблюдался в обеих конфигурациях и связан прежде всего с насыщением узла. </p><p>Новизна работы состоит в раздельной оценке платформенных накладных расходов KubeEdge при неизменной V2X-ориентированной прикладной нагрузке. </p><p>Практическая значимость результатов заключается в возможности использовать полученную оценку как базовый уровень при дальнейшем сравнении фиксированного и адаптивного размещения микросервисов в распределенной cloud–edge-среде и отделять эффект алгоритмов балансировки от затрат инфраструктурного слоя.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Relevance</title><p>Relevance. The development of V2X systems and the migration of computing toward edge and fog nodes require containerization and orchestration mechanisms; however, the overhead introduced by the orchestration platform itself can reduce the benefit of distributed service placement and is particularly important for resource-constrained infrastructure. </p><p>The aim of the study is to estimate the resource cost of using KubeEdge on top of K3s under an identical microservice workload that emulates V2X message processing and to establish a baseline for subsequent evaluation of service placement algorithms. </p></sec><sec><title>Methods</title><p>Methods. A review and systematization of current microservice approaches to V2X, edge, and fog computing were carried out. K3s and K3s + KubeEdge configurations were experimentally compared on the same cloud VPS with unchanged hardware resources, software environment, and five workload profiles from idle to stress. Each profile was executed three times and the obtained results were averaged. CPU utilization, RAM consumption, network traffic, request counts, and the 95th and 99th latency percentiles were measured. </p></sec><sec><title>Results</title><p>Results. Adding KubeEdge increased RAM consumption by approximately 95–105 MB, or 6–8 % relative to K3s. Differences in CPU utilization, network traffic, and latency were minor; the increase in p95/p99 under high load occurred in both configurations and was primarily associated with node saturation. </p></sec><sec><title>Novelty</title><p>Novelty. The study separately evaluates the platform overhead of KubeEdge while keeping the V2X-oriented application workload unchanged. </p></sec><sec><title>Practical significance</title><p>Practical significance. The obtained baseline can be used in further experiments to compare fixed and adaptive microservice placement in a distributed cloud–edge environment and to distinguish the application-level effect of balancing algorithms from orchestration overhead.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>V2X</kwd><kwd>VANET</kwd><kwd>микросервисная архитектура</kwd><kwd>граничные вычисления</kwd><kwd>туманные вычисления</kwd><kwd>K3s</kwd><kwd>KubeEdge</kwd><kwd>оркестрация контейнеров</kwd></kwd-group><kwd-group xml:lang="en"><kwd>V2X</kwd><kwd>VANET</kwd><kwd>microservice architecture</kwd><kwd>edge computing</kwd><kwd>fog computing</kwd><kwd>K3s</kwd><kwd>KubeEdge</kwd><kwd>container orchestration</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Senjab K., Abbas S., Ahmed N., Khan A.R. A survey of Kubernetes scheduling algorithms // Journal of Cloud Computing. 2023. 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