Abstract
This paper proposes a novel event-based k-Nearest Neighbor (kNN) query processing framework using fuzzy sets for distributed sensor systems. Our key technique is that linguistic e-kNN event information instead of raw sensory data is used for e-kNN information storage and in-networks kNN query processing, which is very beneficial to energy efficiency. In addition, event confidence based grid storage method and e-kNN query processing algorithm are devised for e-kNN information storage and retrieval respectively. The experimental evaluation based on real data set show promising results when compared with other methods in the literature.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Chirici, G., Mura, M., McInerney, D., et al.: A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data. Remote Sens. Environ. 176(1), 282–294 (2016)
Islam, R.U.I., Hossain, M.S., Andersson, K.: A novel anomaly detection algorithm for sensor data under uncertainty. Soft Comput. (2016). https://doi.org/10.1007/s00500-016-2425-2
Liu, Y., Fu, J.S., Zhang, Z.: k-Nearest Neighbors tracking in wireless sensor networks with coverage holes. Pers. Ubiquit. Comput. 20(3), 431–446 (2016)
Sharma, G., Busch, C.: Optimal nearest neighbor queries in sensor networks. Theor. Comput. Sci. 608(pt. 2), 146–165 (2015)
Komai, Y., Sasaki, Y., Hara, T., Nishio, S.: k Nearest Neighbor search for location-dependent sensor data in MANETs. Ind. Sens. Netw. Adv. Data Manag. Design Secur. 3(1), 942–954 (2015)
Li, Y.Y., Parker, L.E.: Nearest neighbor imputation using spatial–temporal correlations in wireless sensor networks. Inf. Fusion 15(1), 64–79 (2014)
Lai, Y., Chen, H., Li, C.: Processing the v-kNN queries in wireless sensor networks. In: International Conference on Parallel Processing, pp. 1–6. IEEE, New York (2007)
Zhao, Z., Yu, G., Li, B., Yao, L., Yang, X.: An algorithm for optimizing multidimensional k-NN queries in wireless sensor networks. J. Software 18(5), 1186–1197 (2007). (in Chinese)
Galindo, J.: Handbook of Research on Fuzzy Information Processing in Databases. IGI Global, Hershey (2008)
Zheng, Y., Ling, H., Chen, S., Xue, J.: A hybrid neuro-fuzzy network based on differential biogeography-based optimization for online population classification in earthquakes. IEEE Trans. Fuzzy Syst. 23(4), 1070–1083 (2015)
Rodger, J.A.: A fuzzy nearest neighbor neural network statistical model for predicting demand for natural gas and energy cost savings in public buildings. Expert Syst. Appl. 41(1), 1813–1829 (2014)
Anastasi, G., Conti, M., Francesco, M.D., Passarella, A.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)
Acknowledgements
This work was funded by the Zhejiang Provincial Natural Science Foundation of China (No. LY15F020026, No. LY15F020025), as well as the National Natural Science Foundation of China (No. 61502421).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Li, Y., Lv, M. (2018). Fuzzy-Assisted Event-Based kNN Query Processing in Sensor Networks. In: Li, J., et al. Wireless Sensor Networks. CWSN 2017. Communications in Computer and Information Science, vol 812. Springer, Singapore. https://doi.org/10.1007/978-981-10-8123-1_4
Download citation
DOI: https://doi.org/10.1007/978-981-10-8123-1_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8122-4
Online ISBN: 978-981-10-8123-1
eBook Packages: Computer ScienceComputer Science (R0)
