DocumentCode :
25496
Title :
A Cloud-Friendly RFID Trajectory Clustering Algorithm in Uncertain Environments
Author :
Yanbo Wu ; Hong Shen ; Sheng, Quan Z.
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing, China
Volume :
26
Issue :
8
fYear :
2015
fDate :
Aug. 1 2015
Firstpage :
2075
Lastpage :
2088
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; radiofrequency identification; Internet of Things; IoT; cloud computing resources; cloud-friendly RFID trajectory clustering algorithm; hardware flaws; radio frequency identification tags; transmission faults; Algorithm design and analysis; Cleaning; Clustering algorithms; Data mining; Probabilistic logic; Radiofrequency identification; Trajectory; Internet of Things; cloud computing; clustering algorithm; radio frequency identification (RFID); uncertainty;
fLanguage :
English
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9219
Type :
jour
DOI :
10.1109/TPDS.2014.2347286
Filename :
6877686
Link To Document :
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