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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

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Authors

Xiaolong Xu

Shucun Fu

Lianyong Qi

Xuyun Zhang

Qingxiang Liu

Qiang He

Shancang Li Shancang.Li@uwe.ac.uk
Senior Lecturer in Computer Forensics and Security



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 Mar 29, 2024
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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