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Моделирование и анализ информационных систем

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Иерархические периферийные вычисления

https://doi.org/10.18255/1818-1015-2019-1-146-169

Аннотация

На смену вычислительной парадигме, основанной на giant-like ЦОДах, идет новая, основанная на сети мелких ЦОДов, образующих инфраструктуру для облачных вычислений. Эта смена объективна. Её актуальность обусловлена требованиями новых приложений, активно использующих видео, интерактивность в реальном времени, новые технологии мобильной связи, которые сегодня невозможно реализовать без облачных вычислений и виртуализации на основе технологий SDN&NFV. В статье рассмотрены требования, предъявляемые этими приложениями, предложена архитектура новой парадигмы, которую мы называем «Иерархическими периферийными вычислениями» (Hierarchical Edge Computing – HEC). Показано, что большинство современных приложений являются распределенными совокупностями сервисов реального времени, которые требуют гарантированного качества обслуживания и возможности динамически быть размещенными при работе на периферии сетей разных операторов. Обсуждаются основные научные проблемы, которые необходимо решить для реализации предлагаемой новой парадигмы.

Об авторе

Руслан Леонидович Смелянский
Московский государственный университет имени М.В. Ломоносова
Россия

чл.-кор. РАН, д-р физ.-мат. наук, проф.

Ленинские горы, 1, стр. 52, г. Москва, 119991



Список литературы

1. Bilal K., et al., "Trends and challenges in cloud datacenters", IEEE Cloud Computing, 1:1 (2014), 10-20.

2. Bilal K., et al., "A taxonomy and survey on Green Data Center Networks", Future Generation Computer Systems, 36 (2014), 189-208.

3. Bilal K., Khan S.U., Zomaya A.Y., "Green Data Center Networks: Challenges and Opportunities", IEEE Conference on Frontiers of Information Technology, IEEE, 2013, 229-234.

4. Bilal K., et al., "A survey on green communications using adaptive link rate", Cluster Computing, 16:3 (2013), 575-589.

5. Chen Zhuo, et al., "Early implementation experience with wearable cognitive assistance applications", Proceedings of the 2015 workshop on Wearable Systems and Applications, ACM, 2015, 33-38.

6. Shi Weisong, et al., "Edge computing: Vision and challenges", IEEE Internet of Things Journal, 3:5 (2016), 637-646.

7. "Cisco Global Cloud Index: Forecast and Methodology, 2016-2021", https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.html.

8. "4 Vs of Big Data", http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg.

9. Bonorni F., et al., "Fog computing and its role in the internet of things", Proceedings of the first edition of the MCC workshop T Mobile cloud computing (Helsinki, Finland), 2012, 13-16.

10. Brown B., "Microsoft researcher: Why Micro Datacenters really matter to mobile's future", http://www.networkworld.com/article/2979570/cloud-computing/microsoft-researcher-why-micro-datacenters-really-matter-to-mobiles-future.html.

11. Satyanarayanan M., et al., "The Case for VM-Based Cloudlets in Mobile Computing", IEEE Pervasive Computing, 8:4 (2009), 14 - 23.

12. Aazam M., Huh E., "Dynamic resource provisioning through fog micro datacenter", The 12th IEEE International Workshop on Managing Ubiquitous Communications and Services, 2015, 105-110.

13. Aazam M., Huh E., "Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT", The 29th IEEE International Conference on Advanced Information Networking and Applications (AINA-15), IEEE, 2015, 687-694.

14. Jararweh Y., et al., "The future of mobile cloud computing: Integrating cloudlets and Mobile Edge Computing", 2016 23rd International Conference on Telecommunications (ICT), IEEE, 2016.

15. "Green Clouds", http://www.greenclouds.in/views-and-resources/high-performance-websites/.

16. Giordano A., Spezzano G., Vinci A., "Smart agents and fog computing for smart city applications", International Conference on Smart Cities, Springer, 2016, 137-146.

17. Cortes R., et al., "Stream processing of healthcare sensor data: studying user traces to identify challenges from a big data perspective", Procedia Computer Science, 52 (2015), 1004-1009.

18. Costenaro D., Duer A., "The megawatts behind your megabytes: going from data-center to desktop", 2012 ACEEE Summer Study on Energy Efficiency in Buildings, 2012.

19. "Cisco Data in Motion", https://www.cisco.com/c/m/en_us/solutions/data-center-virtualization/data-motion.html.

20. "MicroDC Solution", https://actfornet.com/HUAWEI_CLOUD_COMPUTING/Huawei%20MicroDC%20Brochure.pdf.

21. "Mobile Edge Computing", http://www.etsi.org/technologies-clusters/technologies/mobile-edge-computing.

22. "Akamai", https://blogs.akamai.com/2016/07/portugal-france-sets-live-sportsdiscretionary{-}{}{}streaming-record-on-akamai.html.

23. Wang Meisong, et al., "An overview of cloud based content delivery networks: research dimensions and state-of-the-art", Transactions on Large-Scale Data-and KnowledgeCentered Systems XX, Springer, 2015, 131-158.

24. Chu Weibo, et al., "Network delay guarantee for diffierentiated services in content-centric networking", Computer Communications, 76 (2016), 54-66.

25. Wang Rui, et al., "Mobility-aware caching for content-centric wireless networks: Modeling and methodology", IEEE Communications Magazine, 54:8 (2016), 77-83.

26. Ahmed Syed Hassan, Bouk Safdar Hussain, Kim Dongkyun, Content-Centric Networks: An Overview, Applications and Research Challenges, Springer, 2016, 108 pp.

27. Gao Ying, et al., Are cloudlets necessary?, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213 USA, 2015, Tech. Rep. CMU-CS-15-139.

28. Bilal K., et al., "Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers", Computer Networks, 130 (2018), 94-120.

29. "TOSCA Simple Profile in YAML Version 1.2", http://docs.oasis-open.org/tosca/TOSCA-Simple-Profile-YAML/v1.2/csprd01/TOSCA-Simple-Profile-YAML-v1.2-csprd01.pdf.

30. Nygren E., Sitaraman R.K., Sun J., "The akamai network: a platform for high-performance internet applications", ACM SIGOPS Operating Systems Review, 44:3 (2010), 2-19.

31. "Data Never Sleeps 2.0", https://www.domo.com/learn/data-never-sleeps-2.

32. Erl T., Service-oriented architecture: concepts, technology, and design, 2005.

33. Antonenko V., et al., "C2: General Purpose Cloud Platform with NFV Life-Cycle Management", 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), IEEE, 2017, 353-356.

34. Petrov I. S., "Mathematical model for predicting forwarding rule counter values in SDN", Young Researchers in Electrical and Electronic Engineering (EIConRus), 2018 IEEE Conference of Russian, IEEE, 2018, 1313-1317.

35. Petrov I., Morgunova O., "Forwarding Rule Minimization for Network Statistics Analysis in SDN", 2018 International Scientific and Technical Conference Modern Computer Network Technologies (MoNeTec), IEEE, 2018, 1-6.

36. Cox J.H., et al., "Advancing software-defined networks: A survey", IEEE Access, 5 (2017), 25487-25526.

37. Chemeritskiy E., Stepanov E., Smeliansky R., "Managing network resources with ow (de) multiplexing protocol", Mathematical and Computational Methods in Electrical Engineering, Recent Advances in Electrical Engineering Series, 53, 2015, 35-43.


Рецензия

Для цитирования:


Смелянский Р.Л. Иерархические периферийные вычисления. Моделирование и анализ информационных систем. 2019;26(1):146-169. https://doi.org/10.18255/1818-1015-2019-1-146-169

For citation:


Smeliansky R.L. Hierarchical Edge Computing. Modeling and Analysis of Information Systems. 2019;26(1):146-169. (In Russ.) https://doi.org/10.18255/1818-1015-2019-1-146-169

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ISSN 1818-1015 (Print)
ISSN 2313-5417 (Online)