Affiliation:
1. Beijing Jiaotong University
Abstract
With the rapid development of high-speed railway, the equipment life-cycle management data are generated in large scales which run through the period of production, operation, maintenance, falling into a notion of Big Data. There is broad recognition of value of data and information obtained through analyzing it. The exponential growth in the amount of railway-related data means that revolutionary measures are needed for data management, analysis and accessibility. At present, the promise of data-driven decision-making is now being recognized broadly. How to store the big data efficiently, reliably and cheaply are important research topics. This paper proposes a framework of data management of high-speed railway equipment, where cloud computing provides a feasible technical solution combined with MapReduce programming model based on Hadoop platform. These models are capable of considering the characteristics of data and processing demand in management of High-speed railway equipment. Finally, we summarize the challenges and opportunities with Big Data for application of China railway and point out there is more than enough that we can work on.
Publisher
Trans Tech Publications, Ltd.
Reference8 articles.
1. Yigitbasi, N., Epema, D. C-Meter: A Framework for Performance Analysis of Computing Clouds,. (CCGRID09), 472-477 (2009).
2. Dean,J. and Ghemawat,S. MapReduce: Simplified data processing on large clusters. In proceedings of Operating Systems Design and Implementation. San Francisco, CA. 137-150(2004).
3. CHEN Kang, ZHENG Weimin. Cloud Computing: System Instances and Current Re-search. Journal of Software. 20(5): 1337-1348(2009) (in Chinese).
4. Yao Qi. Research on Some Key Techniques in Parallelism Security Gateway. 87-95(2010) (in Chinese).
5. Barroso L.A., Holzle,U. The Case for Energy-Proportional Computing. IEEE Computer 40, 12 (2007).
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