Title: A big data based data storage systems for rock burst experiment

Authors: Yu Zhang; Yan-Ping Bai; Dong-Feng Zhu; Zhao-Yong Lv

Addresses: Department of Computer Science, Beijing University of Civil Engineering and Architecture, Beijing, China; State Key Laboratory for GeoMechanics and Deep Underground Engineering, China University of Mining & Technology, Beijing, China ' School of Management, Capital Normal University, Beijing, China ' School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China ' Department of Computer Teaching and Network Information, Beijing University of Civil Engineering and Architecture, Beijing, China

Abstract: State Key Laboratory for GeoMechanics and Deep Underground Engineering, Deep-Lab for short, has been committed to the study of rock burst. Deep-Lab accumulated a large number of rock-burst data. With the deepening of the research progress, massive-data dilemma, artificial-management-data dilemma and experimental-data-analysis dilemma have become three big problems of rock burst. These dilemmas restrict the development of rock burst research technologies. This article takes big data in rock burst experiment as research objects and innovatively introduces big data technology into rock burst. Digital features of rock-burst experimental data were extracted. On this basis, a big data based data storage systems for rock burst experiment, BDSS for short, was designed and built. Then an integrated rock burst experimental platform was constructed. Experiments show that, BDSS solves three dilemmas of rock burst, and realises the distributed storage system of data. BDSS also realises dynamic and efficient load of rock-burst big data, and its efficient query under complication conditions.

Keywords: big data; data storage; rock burst; deep analysis; wireless communications; mobile computing; distributed storage; deep mines.

DOI: 10.1504/IJWMC.2013.057394

International Journal of Wireless and Mobile Computing, 2013 Vol.6 No.5, pp.463 - 472

Received: 27 May 2013
Accepted: 26 Jun 2013

Published online: 28 Oct 2013 *

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