Application and Development of Cloud Computing Technology in Computer Data Processing

Cloud computing is a new technology that represents the realization of an old idea that computer data processing is executed and charged as a service. The goal of this chapter is to define the basics of the cloud computing concept and how this technology works, and then explain where is all the data that cloud computing uses, how they are distributed, how and to what extent are available, who are the ultimate beneficiaries, what are the advantages and the disadvantages of applying this concept. This cloud computing model consists of five essential features, three service models, and four application models, and the elaboration of these concepts will be an integral part of this chapter. Particular attention will be paid to the possibility of data abuse in cloud computing and regarding that data protection against manipulation from service providers as well as the financial aspect of cloud computing.

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Application of Computer Data Processing Technology in Economic Field

Advances in Intelligent Systems and Computing - Cyber Security Intelligence and Analytics ◽

10.1007/978-3-030-43309-3_19 ◽

2020 ◽

pp. 138-144

Author(s):

Yijun Gong

Keyword(s):

Data Processing ◽

Processing Technology ◽

Computer Data ◽

Computer Data Processing

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Cloud Data Management Based on Cloud Computing Technology

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.543-547.3573 ◽

2014 ◽

Vol 543-547 ◽

pp. 3573-3576

Author(s):

Yuan Jun Zou

Keyword(s):

Cloud Computing ◽

Parallel Computing ◽

Data Processing ◽

Development Planning ◽

Computer Data ◽

Cloud Data ◽

Computing Platform ◽

Convergence Error ◽

Cloud Computing Platform ◽

Cloud Data Processing

Cloud computing, networking and other high-end computer data processing technology are the important contents of eleven-five development planning in China. They have developed rapidly in recent years in the field of engineering. In this paper, we combine parallel computing with the collaborative simulation principle, design a cloud computing platform, establish the mathematical model of cloud data processing and parallel computing algorithm, and verify the applicability of algorithm through the numerical simulation. Through numerical calculation, cloud computing platform can be divided into complex grids, and the transmission speed is fast, which is eight times than the finite difference method. The mesh is meticulous, which reaches millions. Convergence error is minimum, only 0.001. The calculation accuracy is up to 98.36%.

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Design of Distributed Network Mass Data Processing System Based on Cloud Computing Technology

10.1109/i-smac52330.2021.9640652 ◽

2021 ◽

Author(s):

Fanghai Gong

Keyword(s):

Cloud Computing ◽

Data Processing ◽

Processing System ◽

Distributed Network ◽

Computing Technology ◽

Data Processing System ◽

Mass Data

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Trends and Technologies in Big Data Processing

Advances in Computational Intelligence and Robotics - Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence ◽

10.4018/978-1-7998-3038-2.ch002 ◽

2020 ◽

pp. 17-42

Author(s):

Amitava Choudhury ◽

Kalpana Rangra

Keyword(s):

Cloud Computing ◽

Big Data ◽

Internet Of Things ◽

Data Processing ◽

Real Time ◽

Computing Technology ◽

Time Data ◽

Big Data Processing ◽

Real Time Data ◽

Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

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