Xiaolong Xu
An IoT-oriented data placement method with privacy preservation in cloud environment
Xu, Xiaolong; Fu, Shucun; Qi, Lianyong; Zhang, Xuyun; Liu, Qingxiang; He, Qiang; Li, Shancang
Authors
Shucun Fu
Lianyong Qi
Xuyun Zhang
Qingxiang Liu
Qiang He
Shancang Li
Abstract
© 2018 Elsevier Ltd IoT (Internet of Things) devices generate huge amount of data which require rich resources for data storage and processing. Cloud computing is one of the most popular paradigms to accommodate such IoT data. However, the privacy conflicts combined in the IoT data makes the data placement problem more complicated, and the resource manager needs to take into account the resource efficiency, the power consumption of cloud data centers, and the data access time for the IoT applications while allocating the resources for the IoT data. In view of this challenge, an IoT-oriented Data Placement method with privacy preservation, named IDP, is designed in this paper. Technically, the resource utilization, energy consumption and data access time in the cloud data center with the fat-tree topology are analyzed first. Then a corresponding data placement method, based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II), is designed to achieve high resource usage, energy saving and efficient data access, and meanwhile realize privacy preservation of the IoT data. Finally, extensive experimental evaluations validate the efficiency and effectiveness of our proposed method.
Citation
Xu, X., Fu, S., Qi, L., Zhang, X., Liu, Q., He, Q., & Li, S. (2018). An IoT-oriented data placement method with privacy preservation in cloud environment. Journal of Network and Computer Applications, 124, 148-157. https://doi.org/10.1016/j.jnca.2018.09.006
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 15, 2018 |
Online Publication Date | Sep 28, 2018 |
Publication Date | Dec 15, 2018 |
Deposit Date | Oct 16, 2018 |
Publicly Available Date | Sep 29, 2019 |
Journal | Journal of Network and Computer Applications |
Print ISSN | 1084-8045 |
Electronic ISSN | 1095-8592 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 124 |
Pages | 148-157 |
DOI | https://doi.org/10.1016/j.jnca.2018.09.006 |
Public URL | https://uwe-repository.worktribe.com/output/855920 |
Publisher URL | https://doi.org/10.1016/j.jnca.2018.09.006 |
Additional Information | Additional Information : This is the author's accepted manuscript. The final published version is available here: https://doi.org/10.1016/j.jnca.2018.09.006. |
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