Jicai Li
ABSTRACT
There are many big data analysis methods, and it is an effective method to build big data analysis model through machine learning. Big data is characterized by large data scale and long calculation cycle. In order to speed up the calculation speed and shorten the calculation cycle, distributed computing method is one of the effective methods to solve the above problems. With the wide application and rapid development of information technology, cloud computing as a new business computing model has attracted more and more attention. However, the security of cloud computing data storage model lacks reliability. Under the mainstream cloud computing and big data basic environment, building a better model from resource aggregation to analysis and mining, and modeling distributed big data analysis can provide high-reliability, high-security, high-efficiency analysis services for practical analysis and mining applications such as intelligence judgment, information deployment and control, stakeholder analysis and intelligent decision-making.
- Zhang Lina, Fan Xingfeng, Zhang Zhilin, Discussion on knowledge management and technological innovation service system based on machine learning. Science Popular, no. 4, pp. 17-21, 2018.Google Scholar
- Yang Tao, Chai Tianyou. Research status and prospects of distributed collaborative optimization. Science in China: Technological Sciences, vol. 50, no. 11, pp. 6-17, 2020.Google Scholar
- Rama Mohanarao Godagili. Artificial Intelligence = Big Data Analysis + Machine Learning + Cloud Computing. Chongqing and the World, vol. 494, no. 18, pp. 33-34, 2018.Google Scholar
- Guo Pengfei, Li Gang. Big data method and its application. Computer Science and Application, vol. 9, no. 9, pp. 1724-1731, 2019.Google ScholarCross Ref
- Liu Yongbo, Li Yaqiong, Zhou Bo, A cloud computing resource scheduling method for distributed machine learning. Computer and Digital Engineering, vol. 47, no. 12, pp. 3059-3062, 3068, 2019.Google Scholar
- Guo Liang, Qi Xu, Liu Shuiwang, Research on key technologies for automatic optimization of data center parameters based on machine learning. Information and Communication Technology and Policy, vol. 312, no. 6, pp. 25-28, 2020.Google Scholar
- Zhang Sufang, Zhai Junhai, Wang Cong, Big Data and Big Data Machine Learning. Journal of Hebei University (Natural Science Edition), vol. 38, no. 3, pp. 81-90+118, 2018.Google Scholar
- Guo Liang, Qi Xu, Liu Shuiwang, Research on key technologies for automatic optimization of data center parameters based on machine learning. Telecommunications Network Technology, no. 6, pp. 21-24, 2020.Google Scholar
- Li Yuting. Distributed big data multi-channel parallel control system in cloud computing environment. Computer measurement and control, vol. 28, no. 10, pp. 121-124+139, 2020.Google Scholar
- Li Shao, Huang Cheng. Simulation of distributed big data intelligent storage algorithm under cloud computing. Computer simulation, vol. 37, no. 5, pp. 448-452, 2020.Google Scholar
- Jin Zihui, Xia Yuhong. Simulation of distributed big data intelligent fusion algorithm under cloud computing. Computer Simulation, 2018, vol. 35, no. 10, pp. 295-298, 2018.Google Scholar
- Zhang Huali, Yang Fan, Yang Huayong. Redundant data distribution algorithm in big data distributed storage under cloud computing. Journal of China Academy of Electronics, vol. 13, no. 4, pp. 433-438, 2018.Google Scholar
- Du Hongjun, Li Wei, Zhang Wenjie, Power big data distributed retrieval system based on cloud computing technology. Power grid and clean energy, vol. 34, no. 9, pp. 23-28, 2018.Google Scholar
- Min Rui. The integrated development and application of artificial intelligence, big data and cloud computing. China High-tech, no. 17, pp. 79-81, 2019.Google Scholar
Recommendations
Cloud computing & big data computing
COM.Geo '12: Proceedings of the 3rd International Conference on Computing for Geospatial Research and ApplicationsThe amount of data each organization deals with today has been rapidly growing. However, analyzing large datasets commonly referred to as "big data" has been a huge challenge due to lack of suitable tools and adequate computing resources. Why are ...
Big data and cloud computing: new wine or just new bottles?
Cloud computing is an extremely successful paradigm of service oriented computing and has revolutionized the way computing infrastructure is abstracted and used. Three most popular cloud paradigms include: Infrastructure as a Service (IaaS), Platform as ...
Big data analytics in Cloud computing: an overview
AbstractBig Data and Cloud Computing as two mainstream technologies, are at the center of concern in the IT field. Every day a huge amount of data is produced from different sources. This data is so big in size that traditional processing tools are unable ...
Comments