Title: High-speed data aggregation storage query method

Authors: Yicheng Mu

Addresses: Department of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China

Abstract: Aiming at the problems of poor aggregation storage capacity and low query efficiency of high-speed data under cloud computing platform, a high-speed data aggregation storage query method based on joint probability density feature extraction and fuzzy C-means clustering under cloud computing platform is proposed. The fused data perturbation is detected and filtered by solving a limited set of vectors, and the fuzzy C-means algorithm is introduced for high-speed data feature clustering to achieve adaptive storage query data. The simulation results show that when the proposed method is used to conduct adaptive query of the data under the cloud computing platform, it can effectively realise the classified querying of data with different attribute categories and the precision ratio and query speed are relatively high, having good application value.

Keywords: cloud computing platform; data; fuzzy C-means clustering; storage; query.

DOI: 10.1504/IJIPT.2019.101366

International Journal of Internet Protocol Technology, 2019 Vol.12 No.3, pp.167 - 172

Received: 18 Oct 2018
Accepted: 27 Nov 2018
Published online: 05 Aug 2019 *

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