Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems
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 uncomm...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2014-03-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/3/5573 |
| _version_ | 1811304685102956544 |
|---|---|
| author | Ruiyun Yu Rui Liu Xingwei Wang Jiannong Cao |
| author_facet | Ruiyun Yu Rui Liu Xingwei Wang Jiannong Cao |
| author_sort | Ruiyun Yu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T08:11:44Z |
| format | Article |
| id | doaj.art-93df5f339db54c83a20d91d2e28e3ec7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:11:44Z |
| publishDate | 2014-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-93df5f339db54c83a20d91d2e28e3ec72022-12-22T02:54:57ZengMDPI AGSensors1424-82202014-03-011435573559410.3390/s140305573s140305573Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing SystemsRuiyun Yu0Rui Liu1Xingwei Wang2Jiannong Cao3Software College, Northeastern University, No. 11, Lane 3, Wenhua Road, Heping District, Shenyang 100819, ChinaDepartment of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, ChinaCollege of Information Science and Engineering, Northeastern University, No. 11, Lane 3, Wenhua Road, Heping District, Shenyang 100819, ChinaDepartment of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, ChinaThe 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.http://www.mdpi.com/1424-8220/14/3/5573participatory sensingreputationcontributiondata quality |
| spellingShingle | Ruiyun Yu Rui Liu Xingwei Wang Jiannong Cao Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems Sensors participatory sensing reputation contribution data quality |
| title | Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems |
| title_full | Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems |
| title_fullStr | Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems |
| title_full_unstemmed | Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems |
| title_short | Improving Data Quality with an Accumulated Reputation Model in Participatory Sensing Systems |
| title_sort | improving data quality with an accumulated reputation model in participatory sensing systems |
| topic | participatory sensing reputation contribution data quality |
| url | http://www.mdpi.com/1424-8220/14/3/5573 |
| work_keys_str_mv | AT ruiyunyu improvingdataqualitywithanaccumulatedreputationmodelinparticipatorysensingsystems AT ruiliu improvingdataqualitywithanaccumulatedreputationmodelinparticipatorysensingsystems AT xingweiwang improvingdataqualitywithanaccumulatedreputationmodelinparticipatorysensingsystems AT jiannongcao improvingdataqualitywithanaccumulatedreputationmodelinparticipatorysensingsystems |