DOI QR코드

DOI QR Code

Recursive PCA-based Remote Sensor Data Management System Applicable to Sensor Network

  • Kim, Sung-Ho (Dept of Electronics and Information Engineering, Kunsan National University) ;
  • Youk, Yui-Su (Dept of Electronics and Information Engineering, Kunsan National University)
  • Published : 2008.06.01

Abstract

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. It has new information collection scheme and monitoring solution for a variety of applications. Faults occurring to sensor nodes are common due to the limited resources and the harsh environment where the sensor nodes are deployed. In order to ensure the network quality of service it is necessary for the WSN to be able to detect the faulty sensors and take necessary actions for the reconstruction of the lost sensor data caused by fault as earlier as possible. In this paper, we propose an recursive PCA-based fault detection and lost data reconstruction algorithm for sensor networks. Also, the performance of proposed scheme was verified with simulation studies.

Keywords

References

  1. D. Estrin, L. Girod, G. Pottie, and M. Srivastava, "Instrumenting the World with Wireless Sensor Networks," in International Conference on Acoustics, Speech, and Signal Processing (ICASSP2001), Salt Lake City, Utah, May 2001
  2. Ia.F, Akyildiz, W. Su, Y. Sankarasubramaniam, E.Cayirci, A Survey on Sensor Networks, IEEE Comunications Magazine, vol.40, no.8, pp.102-114, August 2002
  3. G.J.Pottie and W.J.Kaiser, "Wireless integrated network sensors," Communications of the ACM, vol.43, no.5, pp.51-58, 2000 https://doi.org/10.1145/332833.332838
  4. A.Mainwarning, J.Polastre, R.Szewczyk, and D.Culler, "Wireless sensor networks for habitat monitoring," in First ACM International Workshop on Wireless Sensor Networks and Applications,(Atlanta, GA), Sept. 2002
  5. C.Aubrun, C.Leick, "Sensor Fault Accommodation to an Activated Sludge Process", 2005
  6. Deniz Erdogmus, Yadunandana N. Rao, Hemanth Peddaneni, "RECURSIVE PRINCIPAL COMPONENTS ANALYSIS USING EIGENVECTOR MATRIX PERTURBATION"
  7. Dunia, R. "Identification of faulty sensors using principle component analysis", AIChE J., 42(10), pp. 2797-2812, 1996 https://doi.org/10.1002/aic.690421011
  8. C. Chih-Chen, K. Sze, and Z. Sun, "Structural damage assessment using principal components analysis." Proceedings of the SPIE: Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III. Volume 5394, pp. 438-445, 2004
  9. S. Costa and S. Fiori, "Image compression using principal component neural networks." Image and Vision Computing, Vol. 19, Issues 9-10, 649-668, 2001 https://doi.org/10.1016/S0262-8856(01)00042-7
  10. J. Li and Y. Zhang, "Interactive sensor network data retrieval and management using principal components analysis transform." Journal of Smart Materials and Structures. Vol. 15, No. 6, pp. 1747-1757, 2006 https://doi.org/10.1088/0964-1726/15/6/029