Abstract
With the geometric growth of data generated from complex system test, experiment and condition monitoring, big data has become the hotspot of Industry 4.0 era. How to meet market demand with efficiency, comprehensiveness and low cost through collection and analysis of data is a problem to be solved. We put forward industrial cloud storage model based on Hadoop on the basis of relevant researches and theories of Industry 4.0, big data Hadoop and so on, and then implement and evaluate each module. It performs well in reliability and expandability through test, providing challenges of big data storage in Industry 4.0 era with effective solution.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang, X.: Industry 4.0: intelligent industry. Technol. Internet Things (12), 1–3 (2013). (in Chinese)
Wahlster, W.: From industry 1.0 to industry 4.0: towards the 4th industrial revolution. Forum Business meets Research (2012). (in Chinese)
Yen, C.T., Liu, Y.C., Lin, C.C., et al.: Advanced manufacturing solution to industry 4.0 trend through sensing network and cloud computing technologies. In: 2014 IEEE International Conference on Automation Science and Engineering (CASE), pp. 1150–1152. IEEE (2014). (in Chinese)
Peng, W.: The Key Technology and Application of Cloud Computing, pp. 73–75. The People’s Posts and Telecommunications Publishing House, Beijing (2010). (in Chinese)
Liu, K., Li, A.: Research and implementation of cloud storage based on Hadoop. Micro Comput. Inf. 27(7) (2011). (in Chinese)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008). (in Chinese)
Lin, J., Dyer, C.: Data-intensive text processing with MapReduce. Synth. Lect. Hum. Lang. Technol. 3(1), 1–177 (2010). (in Chinese)
Gao, H., Zhai, Y.: Research of mobile learning model based on hadoop. China Audiovisual Education 2011(288). (in Chinese)
Borthakur, D.: The hadoop distributed file system: architecture and design. Hadoop Proj. Website 11(2007), 21 (2007). (in Chinese)
Cheng, X.: Demands, environment and service of industrial big data under the structure of industrial 4.0. J. Chifeng Uni. (Nat. Sci. Ed.) 2015(4), 14–15. (in Chinese)
Shafer, J., Rixner, S., Cox, A.L.: The hadoop distributed filesystem: balancing portability and performance. In: 2010 IEEE International Symposium on Performance Analysis of Systems & Software (ISPASS), pp. 122–133. IEEE (2010). (in Chinese)
Shvachko, K., Kuang, H., Radia, S., et al.: The hadoop distributed file system. In: 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), pp. 1–10. IEEE (2010). (in Chinese)
Lee, J., Kao, H.A., Yang, S.: Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP 16, 3–8 (2014). (in Chinese)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Geng, K., Liu, L. (2016). Research of Construction and Application of Cloud Storage in the Environment of Industry 4.0. In: Wan, J., Humar, I., Zhang, D. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-44350-8_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-44350-8_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44349-2
Online ISBN: 978-3-319-44350-8
eBook Packages: Computer ScienceComputer Science (R0)