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2020 | OriginalPaper | Chapter

Power Big Data Distributed Retrieval System Based on Cloud Computing Technology

Authors : Yubo Liu, Wenjie Zhang, Jun Qi

Published in: Innovative Computing

Publisher: Springer Singapore

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Abstract

In order to improve the ability of power big data location identification and information fusion, and optimize the design of power big data retrieval system, a design method of power big data retrieval system based on cloud computing technology is proposed. Multi-regression analysis method is used to construct the storage structure model of power large database, analyze the characteristic of the distributed storage data structure of power big data, cluster the information of power big data in the cloud computing environment. The fuzzy feature grouping clustering method is used to detect power big data of different attributes extracts the association rule feature of power big data and realizes power big data distributed retrieval by cloud computing technology. The software of power big data distributed retrieval system is designed in an embedded environment. The simulation results show that the feature directivity of power big data retrieval is better and the data recall rate of data retrieval is higher.

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Literature
1.
Peng, X., D. Deng, S. Cheng, et al. 2015. Key technologies of electric power big data and its application prospects in smart grid. Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering 35 (3): 503–511.
2.
Xue, S., M. Hu, and X. Xu. 2016. Fairness-optimized resource allocation method in cloud environment. Journal of Computer Applications 36 (10): 2686–2691.
3.
Feng, Y., and D. Yue. 2016. Design and implementation of distributed retrieval system for massive power video. Computer Technology and Development 26 (12): 186–189.
4.
Li, C., R. Wang, and J. YU. 2016. Design and implementation of distributed text retrieval system for big data. Computer and Digital Engineering 44 (12): 2426–2430.
5.
Chengchang, Z., Z. Huayu, and L. Jianchang et al. 2018. Massive data analysis of power utilization based on improved K-means algorithm and cloud computing. Journal of Computer Applications.
6.
Wang, Z. Q., and H. L. Li. 2013 Research of massive web log data mining based on cloud computing. In Fifth International Conference on Computational and Information Sciences.
7.
Zhou, D. 2013. Research on ten million of high dimensional data real-time retrieval by multi-GPUs. Bulletin of Science and Technology 29 (1): 118–123.
8.
Li, P., C. Liu, and J. Hai. 2018. Real-time streaming controllable clustering algorithm for correlated big data in cloud computing environment. Science Technology and Engineering 7: 185–190.
9.
LIN, N., and W. Shi. 2014. Web database security index based on multi-layer space fuzzy subtractive clustering algorithm. Computer Science 41 (10): 216–219.
10.
Hu, L., S. Pang, J. Zhu, et al. 2016. FPGA-based big data K-means algorithm optimization. Electric Power Information and Communication Technology 24 (8): 1–6.
Metadata
Title
Power Big Data Distributed Retrieval System Based on Cloud Computing Technology
Authors
Yubo Liu
Wenjie Zhang
Jun Qi
Copyright Year
2020
Publisher
Springer Singapore
Book
Innovative Computing

Print ISBN: 978-981-15-5958-7

Electronic ISBN: 978-981-15-5959-4

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-5959-4_172

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