A Hadoop Processing Method for Massive Sensor Network Data Based on Internet of Things-Reference-Cited by-同舟云学术

A Hadoop Processing Method for Massive Sensor Network Data Based on Internet of Things

Published:2019-09-04 Issue:2 Volume:27 Page:299-306
ISSN:1068-9605
Container-title:International Journal of Wireless Information Networks
language:en
Short-container-title:Int J Wireless Inf Networks

Author:

Zhang Yanxin

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture

Link

http://link.springer.com/content/pdf/10.1007/s10776-019-00455-6.pdf

Reference18 articles.

1. R. D. Fátima, M. R .D. Andrade, A. C. Zucchi, et al., Distributed processing from large scale sensor network using Hadoop. In IEEE International Congress on Big Data, IEEE Computer Society, Washington, D.C., pp. 417–418, 2013.

2. L. Cai, X. Guan, P. Chi, et al., Big data visualization collaborative filtering algorithm based on RHadoop, International Journal of Distributed Sensor Networks, Vol. 11, p. 3, 2015.

3. D. Wu, L. I. Zhuorong, R. Bie, et al., Research on database massive data processing and mining method based on Hadoop cloud platform. In International Conference on Identification, Information and Knowledge in the Internet of Things, IEEE, New York, pp. 107–110, 2015.

4. X. Song, H. He, S. Niu, et al., A data streams analysis strategy based on Hoeffding tree with concept drift on Hadoop system. In International Conference on Advanced Cloud and Big Data, IEEE, New York, pp. 45–48, 2017.

5. B. Li. Study on massive e-government data cloud storage scheme based on Hadoop. In IEEE International Conference on Software Engineering and Service Science, IEEE, New York, pp. 434–437, 2013.

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