The DOI matches its Crossref record.
An IoT-Oriented Data Storage Framework in Cloud Computing Platform
Abstract
The Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of Radio Frequency IDentification (RFID) and wireless sensors devices. Benefiting from RFID and sensor network technology, common physical objects can be connected, and are able to be monitored and managed by a single system. Such a network brings a series of challenges for data storage and processing in a cloud platform. IoT data can be generated quite rapidly, the volume of data can be huge and the types of data can be various. In order to address these potential problems, this paper proposes a data storage framework not only enabling efficient storing of massive IoT data, but also integrating both structured and unstructured data. This data storage framework is able to combine and extend multiple databases and Hadoop to store and manage diverse types of data collected by sensors and RFID readers. In addition, some components are developed to extend the Hadoop to realize a distributed file repository, which is able to process massive unstructured files efficiently. A prototype system based on the proposed framework is also developed to illustrate the framework's effectiveness.
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Citations
Cited by
Digital twin-driven product design, manufacturing and service with big data
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920
Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., & Liljeberg, P. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2017.02.014 · Cited by 1,198
IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges
Cai, H., Xu, B., Jiang, L., & Vasilakos, A. V. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2619369 · Cited by 588
Self-citationIncorporating Intelligence in Fog Computing for Big Data Analysis in Smart Cities
Tang, B., Chen, Z., Hefferman, G., Pei, S., Wei, T., He, H., & Yang, Q. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2679740 · Cited by 353
“Third, the machine-to-machine (M2M) communication among massive numbers of sensors will dominate future communication network traffic, namely Internet of Things (IoT) [11], [12], instead of traditional Internet of Contents in humanto-human and human-to-machine communication.”
BackgroundInternet of things forensics: Recent advances, taxonomy, requirements, and open challenges
Yaqoob, I., Hashem, I. A. T., Ahmed, A., Kazmi, S. M. A., & Hong, C. S. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.09.058 · Cited by 322
Metadata
- Authors
- Jiang, L., Xu, L. D., Cai, H., Jiang, Z., Bu, F., & Xu, B.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2014-05
- Volume
- 10
- Issue
- 2
- Pages
- 1443-1451
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W1997182427
- Cited by
- 352
- References
- 0
- FWCI
- 88.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jiang, L., Xu, L. D., Cai, H., Jiang, Z., Bu, F., & Xu, B. (2014). An IoT-Oriented Data Storage Framework in Cloud Computing Platform. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2014.2306384
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