Sensor Search Based on Sensor Similarity Computing in the Internet of Things

Suyan LIU; Yuanan LIU; Fan WU; Wenhao FAN

doi:10.11999/JEIT171085

Volume 40 Issue 12

Nov. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(12): 3020-3027

Suyan LIU, Yuanan LIU, Fan WU, Wenhao FAN. Sensor Search Based on Sensor Similarity Computing in the Internet of Things[J]. Journal of Electronics & Information Technology, 2018, 40(12): 3020-3027. doi: 10.11999/JEIT171085

Citation:

Suyan LIU, Yuanan LIU, Fan WU, Wenhao FAN. Sensor Search Based on Sensor Similarity Computing in the Internet of Things[J]. Journal of Electronics & Information Technology, 2018, 40(12): 3020-3027. doi: 10.11999/JEIT171085

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Sensor Search Based on Sensor Similarity Computing in the Internet of Things

doi: 10.11999/JEIT171085

Suyan LIU^{1, 2
,
,},
Yuanan LIU¹,
Fan WU^{1, 2},
Wenhao FAN^{1, 2}

1.
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
2.
Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: The National Natural Science Foundation of China (61272518, 61502050), The Beijing Key Laboratory Director Foundation of Work Safety Intelligent Monitoring (Beijing University of Posts and Telecommunications), The YangFan Innovative & Entrepreneurial Research Team Project of Guangdong Province

Received Date: 2017-11-20
Rev Recd Date: 2018-09-12

Available Online: 2018-09-20

Publish Date: 2018-12-01

Abstract

Abstract

The Internet of Things (IoT) is becoming a hot research area, and tens of billions of devices are being connected to the Internet which are advancing on the sensor search service. IoT features (searches are strong spatiotemporal variability, limited resources of the sensor, and mass heterogeneous dynamic data) raise a challenge to the search engines for efficiently and effectively searching and selecting the sensors. In this paper, Piecewise-Linear fitting Sensor Similarity (PLSS) search method is proposed. Based on the content values, PLSS calculates the sensor similarity models to search most similarity sensors. PLSS improves the accuracy and efficiency of search compared with FUZZY set algorithm (FUZZY) and least squares method. PLSS storage costs are at least two order of magnitude less than raw data.
- Internet of Things (IoT),
- Search services,
- Sensor search,
- Sensor similarity computing,
- Piecewise-linear function fitting

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References(19)

References

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