The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model
In order to study the model and system design of music dance resource management, a human nervous system-like fog computing architecture is proposed. Based on the Internet of Things, the music dance resource management system is analyzed, and the contribution model of fog computing resources and the...
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doaj-b6a2a4e2b367448092532b5c39b8c63b2021-03-30T03:05:09ZengIEEEIEEE Access2169-35362020-01-018118401184710.1109/ACCESS.2019.29631998946608The Application of Fog Computing and Internet of Things Technology in Music Resource Management ModelRuizhi Zhang0https://orcid.org/0000-0003-0776-943XSchool of Arts & International Education, Hunan City University, Yiyang, ChinaIn order to study the model and system design of music dance resource management, a human nervous system-like fog computing architecture is proposed. Based on the Internet of Things, the music dance resource management system is analyzed, and the contribution model of fog computing resources and the allocation model of fog computing resources are established. The traditional NSGA-II (Quick Non-dominated Sorting Genetic Algorithms-II) algorithm is improved, and the improved NSGA-II algorithm is obtained to solve the resource allocation problem. Music dance resource management system is designed, implemented and tested. Through simulation and verification, the improved NSGA-II algorithm has better performance in average service delay time and average stability of task execution under different tasks and different fog nodes. In functional testing, the overall situation of music dance resource management system is good, and the design requirements are basically met. In performance testing, the response time is short and the throughput is high. Therefore, the system has high performance, and can meet the large amount of concurrent data access, which makes the user have better experience.https://ieeexplore.ieee.org/document/8946608/Fog computinghuman nervous system-likeInternet of Thingsmusic dance resource management modelresource allocation model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ruizhi Zhang |
spellingShingle |
Ruizhi Zhang The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model IEEE Access Fog computing human nervous system-like Internet of Things music dance resource management model resource allocation model |
author_facet |
Ruizhi Zhang |
author_sort |
Ruizhi Zhang |
title |
The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model |
title_short |
The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model |
title_full |
The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model |
title_fullStr |
The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model |
title_full_unstemmed |
The Application of Fog Computing and Internet of Things Technology in Music Resource Management Model |
title_sort |
application of fog computing and internet of things technology in music resource management model |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
In order to study the model and system design of music dance resource management, a human nervous system-like fog computing architecture is proposed. Based on the Internet of Things, the music dance resource management system is analyzed, and the contribution model of fog computing resources and the allocation model of fog computing resources are established. The traditional NSGA-II (Quick Non-dominated Sorting Genetic Algorithms-II) algorithm is improved, and the improved NSGA-II algorithm is obtained to solve the resource allocation problem. Music dance resource management system is designed, implemented and tested. Through simulation and verification, the improved NSGA-II algorithm has better performance in average service delay time and average stability of task execution under different tasks and different fog nodes. In functional testing, the overall situation of music dance resource management system is good, and the design requirements are basically met. In performance testing, the response time is short and the throughput is high. Therefore, the system has high performance, and can meet the large amount of concurrent data access, which makes the user have better experience. |
topic |
Fog computing human nervous system-like Internet of Things music dance resource management model resource allocation model |
url |
https://ieeexplore.ieee.org/document/8946608/ |
work_keys_str_mv |
AT ruizhizhang theapplicationoffogcomputingandinternetofthingstechnologyinmusicresourcemanagementmodel AT ruizhizhang applicationoffogcomputingandinternetofthingstechnologyinmusicresourcemanagementmodel |
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