Efficient Search Method for IoT Entities with Similarity Adaptive Estimation

Puning ZHANG; Xuyuan KANG; Yuzhe LIU; Xuefang LI; Dapeng WU; Ruyan WANG

doi:10.11999/JEIT190541

Volume 42 Issue 7

Jul. 2020

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Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(7): 1702-1709

Puning ZHANG, Xuyuan KANG, Yuzhe LIU, Xuefang LI, Dapeng WU, Ruyan WANG. Efficient Search Method for IoT Entities with Similarity Adaptive Estimation[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1702-1709. doi: 10.11999/JEIT190541

Citation:

Puning ZHANG, Xuyuan KANG, Yuzhe LIU, Xuefang LI, Dapeng WU, Ruyan WANG. Efficient Search Method for IoT Entities with Similarity Adaptive Estimation[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1702-1709. doi: 10.11999/JEIT190541

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Efficient Search Method for IoT Entities with Similarity Adaptive Estimation

doi: 10.11999/JEIT190541

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Optical Communication and Networks Key Laboratory of Chongqing, Chongqing 400065, China
3.
Ubiquitous Sensing and Networking Key Laboratory of Chongqing, Chongqing 400065, China

Funds: The National Natural Science Foundation (61871062, 61901071), The Program for Innovation Team Building at Institutions of Higher Education in Chongqing (CXTDX201601020), The General Project of Natural Science Foundation of Chongqing (cstc2019jcyj-msxmX0303), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN201800615), The Fifth Supporting Plan for Chongqing's University Excellent Talents (Chongqing Municipal Education Commission, No.29 [2017])

Received Date: 2019-07-18
Rev Recd Date: 2020-03-07

Available Online: 2020-04-11

Publish Date: 2020-07-23

Abstract

Abstract

The existing similar entity search method has poor adaptability to the length of the observed sequence, and the data storage overhead in the search process is too large, and the accuracy of the search result is insufficient. To this end, an efficient search method is proposed for the IoT Entity Search with Similarity Adaptive Estimation (SAEES). Firstly, in order to reduce the storage overhead of the entity observation sequence, a lightweight method of segmentation representation of the observation sequence is designed to perform a lightweight segmentation compression representation of the original observation sequence of the entity collected by the sensor. Then, in order to achieve an accurate estimation of the similarity of entities with different observation sequence lengths, an adaptive estimation method for observation sequence similarity is proposed. Finally, by exploiting the designed efficient similar entity search matching method, the exact search matching of the entity is completed according to the estimated entity similarity. The simulation results show that the proposed method can greatly improve the efficiency of similar entity search.
- Internet of Things (IoT),
- Entity search,
- Similarity,
- Adaptive estimation

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References(21)

References

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