Sensors 2014, 14(3), 5573-5594; doi:10.3390/s140305573
Article

Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems

1,* email, 2email, 3email and 2email
Received: 13 December 2013; in revised form: 20 January 2014 / Accepted: 10 March 2014 / Published: 20 March 2014
(This article belongs to the Section Sensor Networks)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The ubiquity of mobile devices brings forth a sensing paradigm, participatory sensing, to collect and interpret sensory information from the environment. Participants join in multifarious sensing tasks and share their data. The sensing result can be obtained in light of shared data. It is not uncommon that some corrupted data is provided by participants, which makes sensing result unreliable accordingly. To address this nontrivial issue, we proposed the accumulated reputation model (ARM) to improve the accuracy of the sensing result. In ARM, participants’ reputation will be computed and accumulated based on their sensing data. The sensing data from reputable participants make higher contributions to the sensing result. ARM performs well on calculating accurate sensing results, even in extreme scenarios, where there are many inexperienced or malicious participants.
Keywords: participatory sensing; reputation; contribution; data quality
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MDPI and ACS Style

Yu, R.; Liu, R.; Wang, X.; Cao, J. Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems. Sensors 2014, 14, 5573-5594.

AMA Style

Yu R, Liu R, Wang X, Cao J. Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems. Sensors. 2014; 14(3):5573-5594.

Chicago/Turabian Style

Yu, Ruiyun; Liu, Rui; Wang, Xingwei; Cao, Jiannong. 2014. "Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems." Sensors 14, no. 3: 5573-5594.


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