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Approximate Lost Data Recovery Scheme for Data Centric Storage Environments in Wireless Sensor Networks

무선 센서 네트워크 데이터 중심 저장 환경을 위한 소실 데이터 근사 복구 기법

  • 성동욱 (보아스전자(주) 기술연구소) ;
  • 박준호 (충북대학교 정보통신공학부) ;
  • 홍승완 (충북대학교 정보통신공학부) ;
  • 유재수 (충북대학교 정보통신공학부)
  • Received : 2012.02.20
  • Accepted : 2012.03.20
  • Published : 2012.07.28

Abstract

The data centric storage (DCS) scheme is one of representative methods to efficiently store and maintain data generated in wireless sensor networks. In the DCS schemes, each node has the specified data range for storing data. This feature is highly vulnerable to the faults of nodes. In this paper, we propose a new recovery scheme for the lost data caused by the faults of nodes in DCS environments. The proposed scheme improves the accuracy of query results by recovering the lost data using the spatial continuity of physical data. To show the superiority of our proposed scheme, we simulate it in the DCS environments with the faults of nodes. In the result, our proposed scheme improves the accuracy by about 28% through about 2.5% additional energy consumption over the existing scheme.

Keywords

Lost Data Recovery;Data Centric Storage;Wireless Sensor Network

Acknowledgement

Supported by : 농림수산식품부, KISTI

References

  1. X. Li, Y. J. Kim, R. Fovidan, and W. Hong. "Multi-Dimensional Range Queries in Sensor Networks," SenSys'03, 2003.
  2. Y. Lai, H. Chen, and Y. Wang, "Dynamic Balanced Storage in Wireless Sensor Networks," Proc. of the 4th Workshop on Data Management for Sensor Networks: in Conjunction with 33rd International Conference on Very Large Data Bases, pp.7-12, 2007.
  3. M. Aly, K. Pruhs, and P. K. Chrysanthis, "KDDCS: a Load-Balanced In-Network Data-Centric Storage Scheme for Sensor Networks," CIKM'06, pp.317-326, 2006.
  4. W. Heinzelman, "Application-Specific Protocol Architectures for Wireless Networks," PhD Dissertation, Massachusetts Inst. Of Technology, 2000.
  5. X. Tang and J. Xu, "Extending Network Lifetime for Precision-Constrained Data Aggregation in Wireless Sensor Networks," Proc. IEEE INFOCOM, 2006(4).
  6. R. Szewczyk, E. Osterweil, J. Polastre, M. Hamilton, A. Mainwaring, and D. Estrin, "Habitat Monitoring with Sensor Networks," Commun. ACM, pp.34-40, 2004.
  7. Y. Lee, D. Kim, J. Park, D. Seong, J. Yoo, "A Secure Multipath Transmission Scheme Based on One-Way Hash Functions in Wireless Sensor Networks," Journal of Korea Contents Association, Vol.12, No.1, pp.48-58, 2012. https://doi.org/10.5392/JKCA.2012.12.01.048
  8. H. Park, D. Hwang, J. Park, D. Seong, and J. Yoo, "Sensor Positioning Scheme using Density Probability Models in Non-uniform Wireless Sensor Networks," Journal of Korea Contents Association, Vol.12, No.3, pp.55-66, 2012. https://doi.org/10.5392/JKCA.2012.12.03.055
  9. S. Ratnasamy, B. Karp, S. Shenker, D. Estrin, R. Govindan, L. Yin, and F. Yu, "Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table," MONET Vol.8, No.4, 2003.
  10. M. Albano, S. Chessa, F. Nidito, and S. Pelagatti, "Q-NiGHT: Adding QoS to Data Centric Storage in Non-Uniform Sensor Networks," Mobihoc 2006, Vol.1, pp.1-3, 2006.