Error Level Data Fusion Algorithm in WSN

Abstract:

After analysis of the performance of data fusion based on virtual node algorithm (VNB-DF), design of a classification error (EG) the virtual node data fusion algorithm. The algorithm's accuracy depending on the target, set the error level, expressed through the polynomial fitting coefficients of a range of monitoring the distribution of data in memory to generate a virtual node. Experimental results show that compares with the data obtained with the cluster mean and VNB-DF algorithm, the algorithm greatly improves the accuracy of data collection, applications in types of environmental can show a good performance.

• Periodical: Advanced Materials Research (Volumes 403-408)
• Pages: 5303-5307
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.403-408.5303
• Online since: November 2011
• Authors: Yan Kong Yan, Fei Fei Qian, Wen Yi Shen, Ning Ning Qin
• Keywords: Data Fusion, Error Grade, Virtual Node, Wireless Sensor Network (WSN)

References

[1] Li Bian; Qi Zhu. Cooperative Spectrum Sensing Algorithm Based on Date Fusion under Bandwidth Constraints[C] /Proc of the Fifth Internatianal Conference on Natural Computation(ICNC), Tianjing, CN, 2009: 38-42.

DOI: 10.1109/icnc.2009.480

[2] Heinzelman W, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless microsensor networks[C]/Proc of in Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000: 3005-3014.

DOI: 10.1109/hicss.2000.926982

[3] Younis O, Fahmy S. Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach[C]/Proc of in Proceedings of 13th Joint Conference on IEEE Computer and Communications Societies (INFOCOM), Mar. 2004: 629-640.

DOI: 10.1109/infcom.2004.1354534

[4] Guo Jian-quan. Study on data collection of large-scale wireless sensor and actor networks[D]: [Ph.D. Thesis]. Beijin: Tsinghua University, (2010).

[5] Guestrin C, Bodix P, Thibaux R, et al. Distributed regression: an effcient framework for modeling sensor network data[C]/Proc of in Proceedings of IPSN'04, Berkeley, California, 2004: 1-10.

[6] Whei-Min Lin; Ting-Chia Ou. Polynomial Fitting Approach for Wireless Signal Field under Power Lines in Taiwan Railway[C]/Proc of the tenth of IEEE Region Conference, Hong Kong, 2006: 1-4.

DOI: 10.1109/tencon.2006.344101

[7] ZENG Qing-hong, LU De-tang. Curve and Surface Fitting Based on Moving Least-Squares Methods[J]. Journal of Engineering Graphics, 2004, 1(3): 84-87.

[8] Habin Cai, Qiying Cao. An Improved BP Algorithm Based on the Nonlinear Least Square Method and Application in Congestion Control[C]/Proc of the sixth World Congress on Intelligent Control and Automation(WCICA). Dalian, CN, 2006: 2830- 2834.

DOI: 10.1109/wcica.2006.1712881

[9] Shuang-chun Yang; Yi Pan. The Application of the Wireless Sensor Network(WSN) in the Monitoring of Fushun Reach River in China[C]/Proc of the Second International Conference on Computer and Network Technology(ICCNT). Bangkok, 2010: 331-333.

DOI: 10.1109/iccnt.2010.70