The integration strategy of information system based on artificial intelligence big data technology in metaverse environment

The concept of the meta-universe is still in its early stages, but many leading tech companies have invested heavily in research and development for this technology. The development of meta-smart cities is a significant trend. In the meta-universe environment, integrating information systems is cruc...

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Vydáno v:Cluster computing Ročník 27; číslo 5; s. 7049 - 7057
Hlavní autoři: Lin, Yechuan, Liu, Shixing
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.08.2024
Springer Nature B.V
Témata:
Algorithms
Artificial intelligence
Big Data
Cloud computing
Computer Communication Networks
Computer Science
Cost analysis
Data analysis
Data centers
Data collection
Data storage
Efficiency
Health care
Information sharing
Information systems
Medical education
Meta-analysis
Operating Systems
Processor Architectures
R&D
Research & development
Resource scheduling
Silos
Software
Technology assessment
Universe
Virtual reality
Big data
Metaverse
Healthcare information system integration
Distributed computing
Hadoop
ISSN:1386-7857, 1573-7543
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Shrnutí:The concept of the meta-universe is still in its early stages, but many leading tech companies have invested heavily in research and development for this technology. The development of meta-smart cities is a significant trend. In the meta-universe environment, integrating information systems is crucial for analyzing AI big data. Establishing an integrated platform for medical information systems is key to advancing information technology. In the context of the meta-universe, creating an efficient and unified integration platform to eliminate medical information silos and reduce system integration costs has become a pressing issue in medical informatization. This paper proposes a medical information system integration method based on an integration platform and utilizing cloud computing technology as a data center. The core business layer uses the integration software “Ensemble” as the integration platform. The underlying data center employs a Hadoop storage cluster with distributed data storage and parallel computing technology, and the existing scheduling algorithm is studied and analyzed to enhance the resource scheduling algorithm for medical small file data. The effectiveness of the algorithm is simulated and verified on an experimental platform, demonstrating improved efficiency in resource scheduling.
Bibliografie:ObjectType-Article-1
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ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-024-04375-w