Title: Fault-tolerant flexible lossless cluster compression method for monitoring data in smart grid

Authors: Zhijian Qu; Hanlin Wang; Xiang Peng; Ge Chen

Addresses: School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China ' School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China ' State Grid Pingxiang Power Supply Company, Pingxiang 337000, China ' CRRC Corporation Limited, Qingdao 266000, China

Abstract: Big data in smart grid dispatch monitoring systems is susceptible to interference from processing delays and slow response times. Hence, a new fault-tolerant flexible lossless cluster compression method is proposed. This paper presents the Five-tuples (S, D, O, T, M) model, and builds a monitoring data processing platform based on hive. By deploying the dispatch host and monitoring servers under the cloud computing environment, where data nodes are respectively transformed by Deflate, Gzip, BZip2 and LZO lossless compression method. Taking the power dispatch automation system of Long-hai line as example, experimental results show that the cluster lossless compression ratio of BZip2 is greater than 81%; when data records reach twelve million, the compression ratio can be further improved to certain extent by using RCFile storage hive format, which has significant flexible features. Therefore, the new method proposed in this paper can improve the flexibility and fault-tolerant ability of big monitoring data processing in smart grid.

Keywords: cloud computing; smart grid; cluster lossless compression; fault-tolerant.

DOI: 10.1504/IJHPCN.2019.103539

International Journal of High Performance Computing and Networking, 2019 Vol.15 No.1/2, pp.31 - 44

Accepted: 06 Sep 2018
Published online: 08 Nov 2019 *

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