Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/12081
Title: Cloud-fog-edge computing model for video surveillance based on modular arithmetic
Authors: Kuchukov, V. A.
Кучуков, В. А.
Nazarov, A. S.
Назаров, А. С.
Vashchenko, I. S.
Ващенко, И. С.
Keywords: Cloud-fog-edge computing;Residue number system (RNS);Video surveillance system;Fog computing
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Kuchukov, V., Nazarov, A., Vashchenko, I. Cloud-fog-edge Computing Model for Video Surveillance Based on Modular Arithmetic // Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020. - 2020. - Номер статьи 9039458. - Pages 374-376
Series/Report no.: Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020
Abstract: Information management in many areas, such as smart city, smart manufacturing is closely related to the concept of cloud-fog-edge computing. Video surveillance systems in the concept of a smart city can contain thousands of cameras, and the use of a single data center requires significant computing and network resources to ensure the necessary quality of information. The article considers a distributed computing model in which part of video analytics tasks would be performed in the fog, i.e. on the way to the clouds, on peripheral devices. The use of a redundant residue number system (RRNS) will ensure the reliability of calculations. In the article, the choice of parameters is considered, the modeling of distorted information recovery is carried out, and the prospects of using the residue number system and cloud-fog-edge computing for video analytics tasks are presented
URI: http://hdl.handle.net/20.500.12258/12081
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

Files in This Item:
File SizeFormat 
scopusresults 1252 .pdf
  Restricted Access
331.52 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.