The Characteristics of Cloud Computing in the Internet of Things and the Application of Key Technologies
DOI: 10.23977/acss.2024.080215 | Downloads: 4 | Views: 95
Author(s)
Hurxida Yimit 1
Affiliation(s)
1 Hetian Normal College, Hetian, Xinjiang, 848000, China
Corresponding Author
Hurxida YimitABSTRACT
This paper explores the characteristics and key technologies of cloud computing in the Internet of Things (IoT) application. IoT, as an emerging technology, is rapidly evolving and profoundly impacting human life and work. Cloud computing, as one of the fundamental technologies supporting IoT development, provides robust computing and storage support. Firstly, we analyze the characteristics of cloud computing in IoT, including its highly flexible resource scheduling capability, scalability, reliability, and challenges such as security and privacy protection. Next, we introduce key technologies in IoT and cloud computing, including data collection and transmission, storage and computation, edge computing, and virtualization technology. In terms of key technology applications, we delve into encryption algorithms for data security and privacy protection, machine learning and data mining algorithms for big data analysis and mining, and task allocation and scheduling algorithms for edge computing and collaborative processing. Through case studies, we demonstrate the practical application of these key technologies in areas such as smart homes, smart cities, and industrial IoT, and provide insights into the future development trends of cloud computing in IoT, emphasizing the importance of security, intelligence, and sustainable development, to further promote the development of IoT technology.
KEYWORDS
Internet of Things, cloud computing, key technologies, data security, big data analysis, edge computing, smart homes, smart cities, industrial IoT, sustainable developmentCITE THIS PAPER
Hurxida Yimit, The Characteristics of Cloud Computing in the Internet of Things and the Application of Key Technologies. Advances in Computer, Signals and Systems (2024) Vol. 8: 96-107. DOI: http://dx.doi.org/10.23977/acss.2024.080215.
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