Design of BOOKKEEPING Subsystem of LHAASO Project

Article Preview

Abstract:

During the research of cosmic rays in high energy physics, the data produced by real-time observation and simulation experiments is increased all the time. Besides, various physics detector must have description to explain their characteristics. These data become great pressure for the research center. Once LHAASO project officially begins, the data it produced will be approximately several PB. How to store and get data with high rate, along with manage files efficiently, is an important issue.The topic is designing a data management system of LHAASO project. The design will be reference for the engineering of BOOKKEEPING in order to render excellent services for LHAASO project. Its key points are designing friendly and succinct page, using Hadoop platform to distributed store and manage data files, recommending data warehouse principle to associate data source, and uniting Kettle to transform different data files.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1343-1348

Citation:

Online since:

March 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Y. M. Wang, G. H. Feng, Y. Xue, Summary of Hadoop Research in Recent Years in Foreign Countries, Computer Systems and Applications, vol. 22, no. 6, pp.1-5, (2013).

Google Scholar

[2] D. R. Shen, G. Yu, X. T. Wang, T. Z. Nie and Y. Kou, Survey on NoSQL for management of big data, Journal of Software, vol. 24, no. 8, pp.1786-1803, May. (2013).

DOI: 10.3724/sp.j.1001.2013.04416

Google Scholar

[3] Y. He, W. Q. Wang and F. Xue, Study of Massive Data Mining Based on Cloud Computing, Computer technology and development, vol. 23, no. 2, pp.69-72, Feb. (2013).

Google Scholar

[4] B. Huang, S. R. Xu and W. Pu, Design and implementation of MapReduce-based data mining platform, Computer engineering and design, vol. 34, no. 2, Feb. (2013).

Google Scholar

[5] D. W. Sun, G. R. Chang, S. Gao, L. Z. Jin and X. W. Wang, Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments, Journal of computer science and technology, vol. 27, no. 2, Mar. (2012).

DOI: 10.1007/s11390-012-1221-4

Google Scholar

[6] X. P. Qin, H. J. Wang, X. Y. Du and S. Wang, Big Data Analysis—Competition and Symbiosis of RDBMS and MapReduce, Journal of Software, vol. 23, no. 1, pp.32-45, (2012).

DOI: 10.3724/sp.j.1001.2012.04091

Google Scholar

[7] S. Zeng, F. Z. Qi and M. Wang, Study and Implementation of Data Transfer System in Experiment of High Energy Physics, Computer Science, vol. 39, no. 6A, pp.93-95, June. (2012).

Google Scholar

[8] Y. S. Xu, D. S. Zang and G. X. Sun, Design of a distributed file metadata management system, Computer Engineering and Application, vol. 48, no. 7, pp.1-4, Dec. (2012).

Google Scholar

[9] W. Xiong and Z. B. Yu. A Characterization and Analysis of Distributed File Systems, Journal of Integration Technology, vol. 4, no. 1, pp.103-109, Nov. (2012).

Google Scholar

[10] Z. Cao. A future project at tibet: the large high altitude air shower observatory (LHAASO),. Chinese Physics. Vol. 34, no. 2, pp.249-252, Feb. (2010).

DOI: 10.1088/1674-1137/34/2/018

Google Scholar

[11] Y. D. Cheng and A. G. Liu. Research on the Key Technology of Data Management of High Energy Physics Grid, Application Research on Computers. vol. 24, no. 10, pp.1022-1029, Oct. (2007).

Google Scholar

[12] C. Stanescu, Data Collection and Processing for ARGO Yanbajing Experiment, International Conference on Computing in High Energy and Nuclear Physics, Beijing, pp.825-836. (2001).

Google Scholar