An Estimation Algorithm for Missing Data in Wireless Sensor Networks

Nan Yan; Ming-zheng Zhou; Li Tong

doi:10.21307/ijssis-2017-578

.blurhash-client-img { display: none !important; }

An Estimation Algorithm for Missing Data in Wireless Sensor Networks

International Journal on Smart Sensing and Intelligent Systems

Volume 6 (2013): Issue 3 (January 2013)

By: Nan Yan, Ming-zheng Zhou and Li Tong

Open Access

|Jun 2013

Abstract

For estimating the missing data of wireless sensor networks, an estimation algorithm called HD method, which can make use of sensoring space-time correlation of the data, was proposed based on mathematical Hermite and DESM statistical models. The algorithm not only can adaptively adjust the time and space weights, but also can accurately estimate the missing or unavailable data. The experimental results show that the algorithm has good stability and relatively high estimation accuracy.

References

C.-Q. JIN. “urvey on the Management of Uncertain Data”, Communications of CCF, vol.5, no.4, pp.37-42, April 2009.
Search in Google Scholar Back to article
A. F. Salami, H. Bello-Salau, F. Anwar1, A. M. Aibinu , “A Novel Biased Energy Distribution (BED) Technique for Cluster-Based Routing in Wireless Sensor Networks” , International Journal On Smart Sensing and Intelligent Systems, vol.4, no.2,pp.161-173,June 2011.10.21307/ijssis-2017-433
Search in Google Scholar Back to article
J. Pei, M. Hua, Y. F. Tao, and X. M. Lin, “answering techniques on uncertain and probabilistic data: tutorial summary”, Proceedings of 2008 ACM SIGMOD International Conference on Management of Data, Vancouver, pp. 1357-1364, 10-12 June 2008.
Search in Google Scholar Back to article
Kimelfeld B, Kosharovsky Y, Sagiv Y. Query, “efficiency in probabilistic XML models” Proceedings of the 2008 ACM SIGMOD international conference on Management of data. Vancouver, pp.701-714, 10-12 June 2008.10.1145/1376616.1376687
Search in Google Scholar Back to article
Cormode G, Garofalakis M. “Sketching probabilistic data streams”, Proceedings of the 2007 ACM SIGMOD international conference on Management of data. Beijing, pp.281-292, 11-14 June 2007.10.1145/1247480.1247513
Search in Google Scholar Back to article
Ré C, Letchner J, Balazinska M, Suciu D. “Event queries on correlated probabilistic streams”, Proceedings of the 27th ACM SIGMOD international conference on Management of data. Vancouver, pp.715-728, 10-12 June 2008.
Search in Google Scholar Back to article
Y. Li, C. Ai, W. P. Deshmukh, and Y. Wu. “Data estimation in sensor networks using physical and statistical methodologies”, Proceedings of the 28th IEEE International Conference on Distributed Computing Systems. Beijing, China, pp.538-545, 17-20 June 2008.10.1109/ICDCS.2008.22
Search in Google Scholar Back to article
L.-Q. Pan, J.-Z. Li, J.-Z. Luo, “A Temporal and Spatial Correlation Based Missing Values Imputation Algorithm in Wireless Sensor Networks”, Chinese Journal of Computers, vol.33, no.1, pp.1-11, January 2010.10.3724/SP.J.1016.2010.00001
Search in Google Scholar Back to article
F. Pei and X.-L. Han, “Thinning and Optimization of Cubic Hermit Curves”, Computing Technology and Automation, vol.28, no.4, pp.68-71, April 2009.
Search in Google Scholar Back to article
Krishnamachari B., Iyengar S. “Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks”. IEEE Transactions on Computers, vol.53, no.3, pp.241-250, March 2004.10.1109/TC.2004.1261832
Search in Google Scholar Back to article
Chen Q., Lam K. Y., Fan P. “Distributed bayesian algorithms for fault-tolerant event region detection in wireless sensor networks”. IEEE Transactions on Computers, vol.54, no.9, pp.260-264, September 2005.10.1109/TC.2005.140
Search in Google Scholar Back to article
Luo X., Dong M., Huang Y. “On Distributed Fault-Tolerant Detection in Wireless Sensor Networks”. IEEE Transactions on Computers, vol.55, no.1, pp.58-69, January 2006.10.1109/TC.2006.13
Search in Google Scholar Back to article
Ding M., Chen D. et al. “Localized Fault-Tolerant Event Boundary Detection in Sensor Networks”. Annual IEEE Conference on Computer Communications (INFOCOM), Miami, pp.840-844, 13-15 March 2005.
Search in Google Scholar Back to article
Ian F. A., Weilian S. et al. “A Survey on Sensor Networks”. IEEE Communications Magazine, pp.102-114, August 2002.10.1109/MCOM.2002.1024422
Search in Google Scholar Back to article
J.-P. Yang, Q. Li, Z. Liu, X.-L. Yuan, “Research of improved BP algorithm based on self-adaptive learning rate”, Computer Engineering and Applications, vol.45, no.11, pp.56-58, November 2009.
Search in Google Scholar Back to article
S. Madden, Intel Berkeley research lab data, http://berkeley.intelresearch.net/labdata, 2003.
Search in Google Scholar Back to article
S.S. Ahuja, S. Ramasubramanian, and M.M. Krunz. “Single-link failure detection in all- optical networks using monitoring cycles and paths”, IEEE/ACM Transactions on Networking, vol.17, no.4, pp.1080–1093, April 2009.
Search in Google Scholar Back to article
R. Tan, G. Xing, Z. Yuan, X. Liu, and J. Yao. “System-level calibration for fusion based wireless sensor networks”, In Proceedings of IEEE RTSS, San Diego, CA, USA, pp.143-231, 30 November- 3 December 2010.
Search in Google Scholar Back to article
X. Wang, L. Fu, and C. Hu. “Multicast performance with hierarchical cooperation”. IEEE/ACM Transactions on Networking, vol.20, no.3, pp.1-4, March 2011.10.1109/TNET.2011.2170584
Search in Google Scholar Back to article
Z. Li, M. Li, J. Wang, and Z. Cao. “Ubiquitous data collection for mobile users in wireless sensor networks”, In Proceedings of IEEE INFOCOM, Shanghai, China. pp.230-234, 10-15 April 2011.10.1109/INFCOM.2011.5935040
Search in Google Scholar Back to article
K. Liu, Q. Ma, X. Zhao, and Y. Liu. “Self-diagnosis for large scale wireless sensor networks”. In Proceedings of IEEE INFOCOM, Shanghai, China, pp.350-354, 10-15 April 2011.10.1109/INFCOM.2011.5934944
Search in Google Scholar Back to article
S. Liu, G. Xing, H. Zhang, J. Wang, J. Huang, M. Sha, and L. Huang. “Passive interference measurement in wireless sensor networks”. In Proceedings of IEEE ICNP, Kyoto, Japan, pp.430-433, 5-8 October 2010.10.1109/ICNP.2010.5762754
Search in Google Scholar Back to article
Y. Liu, K. Liu, and M. Li. “Passive diagnosis for wireless sensor networks”. IEEE/ACM Transactions on Networking, vol.18, no.4, pp.1132–1144, April 2010.
Search in Google Scholar Back to article
E. Magistretti, O. Gurewitz, and E. Knightly. “Inferring and mitigating a link’s hindering transmissions in managed 802.11 wireless networks”. In Proceedings of ACM MobiCom, Chicago, Illinois, USA. pp.1221-1224, 20-24 September 2010.
Search in Google Scholar Back to article
A.-Y. Zhou, C.-Q. Jin, G.-R. Wang, and J.-Z. LI, “A Survey on the Management of Uncertain Data”, Chinese Journal of Computers, vol. 32, no.1, pp.1-16, January 2009.10.3724/SP.J.1016.2009.00001
Search in Google Scholar Back to article
Q. Ma, K. Liu, X. Miao, and Y. Liu. “Sherlock is around: Detecting network failures with local evidence fusion”, In Proceedings of IEEE INFOCOM, Orlando, FL, USA, pp.320-329, 25-30 March 2012.10.1109/INFCOM.2012.6195826
Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.21307/ijssis-2017-578 | Journal eISSN: 1178-5608

Journal RSS Feed

Language: English

Page range: 1032 - 1053

Submitted on: Sep 19, 2012

Accepted on: May 7, 2013

Published on: Jun 5, 2013

Published by: Macquarie University, Australia

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Wireless sensor network,

missing data,

mathematical model,

estimation algorithm,

spacetime correlation

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2013 Nan Yan, Ming-zheng Zhou, Li Tong, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 6 (2013): Issue 3 (January 2013)