Foggy computing and their mathematical modeling
Foggy computing complements the centralized cloud model. The main purpose of nebulous computing is to bring functional computing nodes closer to users. Bringing data processing and storage closer to end users allows you to solve many problems that arise with the exponential growth of the number of d...
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| Дата: | 2021 |
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| Формат: | Стаття |
| Мова: | Ukrainian |
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Інститут проблем реєстрації інформації НАН України
2021
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| Онлайн доступ: | http://drsp.ipri.kiev.ua/article/view/244787 |
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| Назва журналу: | Data Recording, Storage & Processing |
Репозитарії
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drspiprikievua-article-244787 |
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Data Recording, Storage & Processing |
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2021-12-14T03:35:52Z |
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Ukrainian |
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reference architecture foggy fog computing infrastructure node models service characteristics failures priority service disciplines |
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reference architecture foggy fog computing infrastructure node models service characteristics failures priority service disciplines Матов, О. Я. Foggy computing and their mathematical modeling |
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еталонна архітектура інфраструктура туманних обчислень моделі вузлів характеристики обслуговування відмови пріоритетні дисципліни обслуговування reference architecture foggy fog computing infrastructure node models service characteristics failures priority service disciplines |
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Article |
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Матов, О. Я. |
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Матов, О. Я. |
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Матов, О. Я. |
| title |
Foggy computing and their mathematical modeling |
| title_short |
Foggy computing and their mathematical modeling |
| title_full |
Foggy computing and their mathematical modeling |
| title_fullStr |
Foggy computing and their mathematical modeling |
| title_full_unstemmed |
Foggy computing and their mathematical modeling |
| title_sort |
foggy computing and their mathematical modeling |
| title_alt |
Туманні обчислення та їхнє математичне моделювання |
| description |
Foggy computing complements the centralized cloud model. The main purpose of nebulous computing is to bring functional computing nodes closer to users. Bringing data processing and storage closer to end users allows you to solve many problems that arise with the exponential growth of the number of devices connected to the network.
The reference nebulous computing architecture OpenFog Reference Architecture was proposed by the international consortium OpenFog Consortium. And in 2018, the IEEE Standards Association adopted this architecture as the official standard.
The new IEEE 1934 standard regulates the use of a reference architecture as a universal techno-logy platform to support applications that require processing huge amounts of data, including the Internet of Things (IoT), industrial Internet (Industrial Internet of Things, IIoT), artificial intelligence, networks 5G and a number of other modern technologies.
According to the consortium, digital innovations of the modern world — IoT, artificial intelligence, virtual reality, tactile Internet, 5G networks — can radically change production processes, business and people's lives. However, moving zetatabytes of data generated by connected businesses, buildings, hospitals, and cars can lead to many problems in traditional cloud infrastructures.
The transfer to the cloud of huge arrays of data, their processing, the formation of control effects and their delivery in a reasonable time require very high performance from cloud resources and the widest bandwidth from the «end-to-end» network infrastructure. However, the construction, maintenance and development of such systems are associated with huge costs.
Fog computing technology eliminates the limitations of centralized cloud solutions by providing the resources and communication channels needed for specific tasks. The concept and technological principles of the architecture of nebulous computing are given.
Analytical models of nebulous computing for calculation of their characteristics with use of many streams and many priorities of applications for the decision of problems, various disciplines of service and their combinations, taking into account failures and various disciplines of additional service and accumulation in queues for time of restoration of the service device) have been considered. The models use an arbitrary law of distribution of random values of maintenance and restoration of the maintenance node, which provides additional opportunities in the study of specific nebulous calculations. Refs: 6 titles. |
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Інститут проблем реєстрації інформації НАН України |
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2021 |
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http://drsp.ipri.kiev.ua/article/view/244787 |
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AT matovoâ foggycomputingandtheirmathematicalmodeling AT matovoâ tumanníobčislennâtaíhnêmatematičnemodelûvannâ |
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2025-07-17T10:58:28Z |
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drspiprikievua-article-2447872021-12-14T03:35:52Z Foggy computing and their mathematical modeling Туманні обчислення та їхнє математичне моделювання Матов, О. Я. еталонна архітектура, інфраструктура туманних обчислень, моделі вузлів, характеристики обслуговування, відмови, пріоритетні дисципліни обслуговування reference architecture, foggy fog computing infrastructure, node models, service characteristics, failures, priority service disciplines Foggy computing complements the centralized cloud model. The main purpose of nebulous computing is to bring functional computing nodes closer to users. Bringing data processing and storage closer to end users allows you to solve many problems that arise with the exponential growth of the number of devices connected to the network. The reference nebulous computing architecture OpenFog Reference Architecture was proposed by the international consortium OpenFog Consortium. And in 2018, the IEEE Standards Association adopted this architecture as the official standard. The new IEEE 1934 standard regulates the use of a reference architecture as a universal techno-logy platform to support applications that require processing huge amounts of data, including the Internet of Things (IoT), industrial Internet (Industrial Internet of Things, IIoT), artificial intelligence, networks 5G and a number of other modern technologies. According to the consortium, digital innovations of the modern world — IoT, artificial intelligence, virtual reality, tactile Internet, 5G networks — can radically change production processes, business and people's lives. However, moving zetatabytes of data generated by connected businesses, buildings, hospitals, and cars can lead to many problems in traditional cloud infrastructures. The transfer to the cloud of huge arrays of data, their processing, the formation of control effects and their delivery in a reasonable time require very high performance from cloud resources and the widest bandwidth from the «end-to-end» network infrastructure. However, the construction, maintenance and development of such systems are associated with huge costs. Fog computing technology eliminates the limitations of centralized cloud solutions by providing the resources and communication channels needed for specific tasks. The concept and technological principles of the architecture of nebulous computing are given. Analytical models of nebulous computing for calculation of their characteristics with use of many streams and many priorities of applications for the decision of problems, various disciplines of service and their combinations, taking into account failures and various disciplines of additional service and accumulation in queues for time of restoration of the service device) have been considered. The models use an arbitrary law of distribution of random values of maintenance and restoration of the maintenance node, which provides additional opportunities in the study of specific nebulous calculations. Refs: 6 titles. Туманні обчислення доповнюють хмарні обчислення, територіально наближують вузли обробки та зберігання даних до користувачів. За рахунок скорочення трафіка це дозволяє уникнути безлічі проблем у традиційних хмарних інфраструктурах, які можуть виникнути в разі необхідності переміщення зеттабайтних обсягів даних. Одночасно скорочується час доставки рішень задач користувачів. Запропоновано аналітичні моделі туманних обчислень для вирахування характеристик з використанням багатьох потоків і багатьох пріоритетів зая-вок на рішення задач, різних дисциплін обслуговування та їхніх комбінацій з урахуванням відмов і різних дисципліни дообслуговування та накопичення в чергах на час відновлення. Інститут проблем реєстрації інформації НАН України 2021-09-21 Article Article application/pdf http://drsp.ipri.kiev.ua/article/view/244787 10.35681/1560-9189.2021.23.3.244787 Data Recording, Storage & Processing; Vol. 23 No. 3 (2021); 22-43 Регистрация, хранение и обработка данных; Том 23 № 3 (2021); 22-43 Реєстрація, зберігання і обробка даних; Том 23 № 3 (2021); 22-43 1560-9189 uk http://drsp.ipri.kiev.ua/article/view/244787/244539 Авторське право (c) 2021 Реєстрація, зберігання і обробка даних |