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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">ntv</journal-id><journal-title-group><journal-title xml:lang="ru">Научно-технический вестник информационных технологий, механики и оптики</journal-title><trans-title-group xml:lang="en"><trans-title>Scientific and Technical Journal of Information Technologies, Mechanics and Optics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2226-1494</issn><issn pub-type="epub">2500-0373</issn><publisher><publisher-name>Университет ИТМО</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17586/2226-1494-2024-24-5-815-823</article-id><article-id custom-type="elpub" pub-id-type="custom">ntv-152</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 СИСТЕМЫ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>COMPUTER SCIENCE</subject></subj-group></article-categories><title-group><article-title>Гарантированные оценки гамма-процентного остаточного ресурса оборудования систем хранения данных</article-title><trans-title-group xml:lang="en"><trans-title>Guaranteed estimates of the gamma percent residual life of data storage equipment</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4191-1348</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ломакин</surname><given-names>М. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Lomakin</surname><given-names>M. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ломакин Михаил Иванович - доктор технических наук, доктор экономических наук, профессор, главный научный сотрудник</p><p>Москва, 121352</p></bio><bio xml:lang="en"><p>Mikhail I. Lomakin - D.Sc., D.Sc. (Economics), Professor, Chief Researcher</p><p>Moscow, 121352</p></bio><email xlink:type="simple">lomakin@vniigochs.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/0000-0002-3342-8770</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Докукин</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Dokukin</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Докукин Александр Владимирович - доктор экономических наук, главный научный сотрудник</p><p>Москва, 121352</p></bio><bio xml:lang="en"><p>Alexander V. Dokukin - D.Sc. (Economics), Chief Researcher</p><p>Moscow, 121352</p></bio><email xlink:type="simple">dokukin@vniigochs.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/0000-0002-2178-5033</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Олтян</surname><given-names>И. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Oltyan</surname><given-names>I. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Олтян Ирина Юрьевна - кандидат технических наук, ученый секретарь</p><p>Москва, 121352</p></bio><bio xml:lang="en"><p>Irina Yu. Oltyan - PhD, Scientific Secretary</p><p>Moscow, 121352</p></bio><email xlink:type="simple">oltyan@vniigochs.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/0000-0001-5589-4855</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ниязова</surname><given-names>Ю. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Niyazova</surname><given-names>Yu. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ниязова Юлия Михайловна - кандидат экономических наук, доцент</p><p>Москва, 105064</p></bio><bio xml:lang="en"><p>Yulia M. Niyazova - PhD (Economics), Associate Professor</p><p>Moscow, 105064</p></bio><email xlink:type="simple">y_niyazova@edu.miigaik.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Всероссийский научно-исследовательский институт по проблемам гражданской обороны и чрезвычайных ситуаций МЧС России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>All-Russian Scientific Research Institute for Civil Defense and Emergencies of the EMERCOM of Russia</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Московский государственный университет геодезии и картографии</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Moscow State University of Geodesy and Cartography</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>14</day><month>12</month><year>2024</year></pub-date><volume>24</volume><issue>5</issue><fpage>815</fpage><lpage>823</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ломакин М.И., Докукин А.В., Олтян И.Ю., Ниязова Ю.М., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Ломакин М.И., Докукин А.В., Олтян И.Ю., Ниязова Ю.М.</copyright-holder><copyright-holder xml:lang="en">Lomakin M.I., Dokukin A.V., Oltyan I.Y., Niyazova Y.M.</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://ntv.elpub.ru/jour/article/view/152">https://ntv.elpub.ru/jour/article/view/152</self-uri><abstract><p>Введение. Активное развитие цифровых технологий, технологии интернета вещей, виртуальных испытаний требуют увеличения объемов собираемой и используемой информации, которая размещается в системах хранения данных (СХД). Стремительный рост объема данных ведет к ужесточению требований к СХД, например, основного их них — повышение надежности хранения больших объемов информации. Данное требование предполагает необходимость оценки надежности оборудования СХД. Для этих целей требуется оценка таких показателей надежности как вероятность безотказной работы, вероятность отказов, средний остаточный ресурс, гамма-процентный ресурс. Традиционно показатели надежности оцениваются при экспоненциальном распределении времени отказа. В реальной ситуации выборки времени отказов оборудования СХД являются малыми, по которым невозможно однозначно идентифицировать исходное распределение. В работе предложена модель оценки показателей надежности как гамма-процентный остаточный ресурс в условиях неполных данных, представленных малыми выборками случайных величин времени безотказной работы оборудования. Научная новизна работы состоит в получении общего решения задачи определения гарантированного гамма-процентного остаточного ресурса оборудования в условиях неполных данных, представленной малыми выборками наработок до отказа оборудования.Метод. Математическая формализация задачи оценки гамма-процентного остаточного ресурса оборудования СХД в условиях неполных данных, представленных малыми выборками, выполнена в виде модели стохастического уравнения. Решением уравнения является гарантированная (нижняя, верхняя) оценка гамма-процентного остаточного ресурса оборудования.Основные результаты. Предложена модель оценки гамма-процентного остаточного ресурса оборудования СХД в условиях неполных данных. Решена в общем случае задача нахождения гарантированных (нижних и верхних) оценок гамма-процентного остаточного ресурса оборудования на множестве функций распределения времени безотказной работы оборудования с заданными моментами, равными выборочным моментам, определяемым по малым выборкам. При двух моментах времени безотказной работы оборудования получены аналитические соотношения для определения гамма-процентного остаточного ресурса. Работоспособность модели продемонстрирована на примере определения нижней гарантированной оценки гамма-процентного остаточного ресурса модели дискового массива HP EVA P6500.Обсуждение. Полученные результаты могут быть использованы специалистами при оценке и оптимизации гамма-процентного остаточного ресурса оборудования СХД.</p></abstract><trans-abstract xml:lang="en"><p>The active development of digital technologies, Internet of Things technologies, and virtual tests requires an increase in the volume of information collected and used, which is placed in data storage systems. The rapid growth of data volume leads to stricter requirements for storage. One of the main requirements for storage is to increase the reliability of storing large amounts of information. This implies the need to assess the reliability of storage equipment. For these purposes, it is necessary to evaluate such reliability indicators as the probability of failure-free operation, the probability of failures, the average residual resource, and the gamma percent resource. Traditionally, reliability indicators are evaluated with an exponential distribution of failure time. In a real situation, the samples of failure times of storage equipment are small, for which it is impossible to uniquely identify the initial distribution. In this article, a model is proposed for evaluating reliability indicators as a gamma percent residual resource in conditions of incomplete data presented by small samples of random variables of equipment uptime. The scientific novelty of the presented work consists in obtaining a general solution to the problem of determining the guaranteed gamma percent residual life of equipment in conditions of incomplete data presented by small samples of developments before equipment failure. The mathematical formalization of the problem of estimating the gamma percent residual life of storage equipment in conditions of incomplete data presented by small samples is performed in the form of a stochastic equation model, the solution of which is a guaranteed (lower, upper) estimate of the gamma percent residual life of equipment. A model for estimating the gamma percent residual life of storage equipment in conditions of incomplete data is presented. In the general case, the problem of finding guaranteed (lower and upper) estimates of the gamma percent residual life of equipment on a set of functions for the distribution of uptime of equipment with specified moments equal to sample moments determined from small samples is solved. At two points in the uptime of the equipment, analytical ratios were obtained to determine the gamma percent residual life. The performance of the model is demonstrated by the example of determining the lower guaranteed estimate of the gamma percent residual resource of the HP EVA P6500 disk array model. The results obtained can be used by specialists in evaluating and optimizing the gamma percent residual life of storage equipment.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>система хранения данных</kwd><kwd>гамма-процентный ресурс</kwd><kwd>модель</kwd><kwd>моменты распределения</kwd><kwd>вероятность</kwd><kwd>гарантированные оценки</kwd></kwd-group><kwd-group xml:lang="en"><kwd>data storage system</kwd><kwd>gamma percentage resource</kwd><kwd>model</kwd><kwd>distribution moments</kwd><kwd>probability</kwd><kwd>guaranteed estimates</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">Глобальный кризис хранения данных. Почему места в хранилищах на всех не хватит [Электронный ресурс]. URL: https://habr.com/ru/companies/first/articles/710838/ (дата обращения: 17.04.2024).</mixed-citation><mixed-citation xml:lang="en">The global data storage crisis. 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