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The Characteristics of Cloud Computing in the Internet of Things and the Application of Key Technologies

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DOI: 10.23977/acss.2024.080215 | Downloads: 4 | Views: 90

Author(s)

Hurxida Yimit 1

Affiliation(s)

1 Hetian Normal College, Hetian, Xinjiang, 848000, China

Corresponding Author

Hurxida Yimit

ABSTRACT

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 development

CITE 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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