Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/97430
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Type: | Journal article |
Title: | A cloud-friendly RFID trajectory clustering algorithm in uncertain environments |
Author: | Wu, Y. Shen, H. Sheng, Q. |
Citation: | IEEE Transactions on Parallel and Distributed Systems, 2015; 26(8):2075-2088 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Issue Date: | 2015 |
ISSN: | 1045-9219 1558-2183 |
Statement of Responsibility: | Yanbo Wu, Hong Shen, and Quan Z. Sheng |
Abstract: | In the emerging environment of the Internet of Things (IoT), through the connection of billions of radio frequency identification (RFID) tags and sensors to the Internet, applications will generate an unprecedented number of transactions and amount of data that require novel approaches in mining useful information from RFID trajectories. RFID data usually contain a considerable degree of uncertainty caused by various factors such as hardware flaws, transmission faults and environment instability. In this paper, we propose an efficient clustering algorithm that is much less sensitive to noise and outliers than the existing methods. To better facilitate the emerging cloud computing resources, our algorithm is designed cloud-friendly so that it can be easily adopted in a cloud environment. The scalability and efficiency of the proposed algorithm are demonstrated through an extensive set of experimental studies. |
Keywords: | Internet of Things; cloud computing; clustering algorithm; radio frequency identification (RFID); uncertainty |
Description: | Date of Publication: 13 August 2014 |
Rights: | © 2014 IEEE |
DOI: | 10.1109/TPDS.2014.2347286 |
Published version: | http://dx.doi.org/10.1109/tpds.2014.2347286 |
Appears in Collections: | Aurora harvest 7 Computer Science publications |
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RA_hdl_97430.pdf Restricted Access | Restricted Access | 1.29 MB | Adobe PDF | View/Open |
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