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Reseach Article

Estimation based Efficient and Resilient Hierarchical In-Network Data Aggregation Scheme for Wireless Sensor Network

by N. Chitradevi, V.Palanisamy, K. Baskaran, K. Swathithya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 25
Year of Publication: 2010
Authors: N. Chitradevi, V.Palanisamy, K. Baskaran, K. Swathithya
10.5120/453-756

N. Chitradevi, V.Palanisamy, K. Baskaran, K. Swathithya . Estimation based Efficient and Resilient Hierarchical In-Network Data Aggregation Scheme for Wireless Sensor Network. International Journal of Computer Applications. 1, 25 ( February 2010), 81-85. DOI=10.5120/453-756

@article{ 10.5120/453-756,
author = { N. Chitradevi, V.Palanisamy, K. Baskaran, K. Swathithya },
title = { Estimation based Efficient and Resilient Hierarchical In-Network Data Aggregation Scheme for Wireless Sensor Network },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 25 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 81-85 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number25/453-756/ },
doi = { 10.5120/453-756 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:48:38.791705+05:30
%A N. Chitradevi
%A V.Palanisamy
%A K. Baskaran
%A K. Swathithya
%T Estimation based Efficient and Resilient Hierarchical In-Network Data Aggregation Scheme for Wireless Sensor Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 25
%P 81-85
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In a large sensor network, in-network data aggregation is inherently used as a communication paradigm which reduces the number of packets transmitted and hence the energy consumed. However the unattended and hostile operation of sensor network makes the system vulnerable to node compromise attack. The compromised nodes can inject false data in to the network which deteriorates the accuracy of the aggregate data. So the research on resilient data aggregation with a focus on data integrity and accuracy becomes a major issue. In this paper, we propose a statistical based robust estimate to design a resilient in-network aggregation scheme which detects and isolates the outliers from computed aggregate value. Simulation results demonstrate that our approach provides a powerful mechanism for detecting outliers even in the presence of multiple compromised nodes.

References
  1. Adrian Perrig, Robert Szewczyk, Victor Wen, David Culler and J.D. Tygar. SPINS: Security Protocols for Sensor Networks. In Wireless Networks Jounal (WINET), 8(5):521-279,1981.
  2. Adrian Perrig, Ran Cnetti, J.D. Tygar, and Dawn Song. The TESLA Broadcast Authentication Protocol. RSA CryptoBytes, 2002.
  3. Antonios Deligiannakis et al. Outlier-Aware Data Aggregation in Sensor Networks, In ICDE, 2008.
  4. A. Boulis, S. Ganeriwal, and M.B. Srivastava. Aggregation in Sensor Networks: An Energy- Accuracy Trade-Off. In Proc. 2003 IEEE Int'l Workshop Sensor Network Protocols and Applications, pp. 128- 138,2003.
  5. V. Barnett and T. Lewis Outliers in Statistical Data. John Wiley & Sons, 1994.
  6. . J. Chou, D. Petrovic, and K. Ramchandran. A Distributed and Adaptive Signal Processing Approach to Reducing Energy Consumption in Sensor Networks. In Proc. IEEE INFOCOM 2003, vol.2, pp.1054-1062, 2003.
  7. C. Castelluccia, E. Mykletun, and G. Tsudik. Efficient Aggregation of Encrypted Data in Wireless S ensor Networks. In Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'05),2005.
  8. J.Y. Chen, G. Pandurangan, and D. Xu. Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis. In Proceedings of the International Symposium on Information Processing in Sensor Networks (IPSN'05). 348-355,2005.
  9. David Wagner. Resilient Aggregation in Sensor Networks. In Workshop on Security of Ad Hoc and Sensor Networks, 2004.
  10. A. Deligiannakis, Y. Kotidis, and N. Roussopoulos. Bandwidth Constrained Queries in Sensor Networks. In VLDB Journal, 2007.
  11. S. Ganeriwal, M.B. Srivastava. Reputation-based Framework for High Integrity Sensor Networks. In ACM Security for Ad-hoc and Sensor Networks (SASN 2004).
  12. Hodge V, and Austin J. A Survey of Outlier Detection Methodologies. In Artificial Intelligence Review, 22:85- 126. 2004.
  13. C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann and F. Silva. Directed Diffusion for Wireless Sensor Networking. In IEEE/ACM Trans. Networking, vol.11, no.1, pp 2-16, 2003.
  14. B. Krishnamachari, D. Estrin, and S. Wicker. The impact of data aggregation in Wireless Networks. In Internationl Workshop on Distributed Event-Based Systems, (DEBS '02), Vienna, Austria, 2002.
  15. L. Lamport, R. Shostak, and M. Pease. The Byzantine Generals Problem. In ACM Transactions on Programming Languages and Systems, Vol. 4, No.3, 1982.
  16. S. Olariu, A. Wada, L. Wilson, and M. Eltoweissy. Wireless Sensor Networks: Leveraging the Virtual Infrastucture. In IEEE Network, vol. 18, no. 4, pp.51-56, . 2004.
  17. S. Pattem, B. Krishnamachar, and R. Govindan. The Impact of Spatial Correlation on Routing with compression in Wireless Sensor Networks. In Proc. Third International Symposium. Information Processing in Sensor Networks (IPSN), pp.28-35, 2004.
  18. 18] Péter Schaffer et al. Correlation-based Resilient Aggregation in Sensor Networks. In MSWiM'07, October 22-26, 2007.
  19. B. Przydatek, D. Song, and A. Perrig. SIA: Secure Information Aggregation in Sensor Networks. In SenSys '03: Proceedings of the 1st International Conference on Embedded Networked Sensor System, pp.225-265,2003.
  20. A. Sharaf, J. Beaver, A. Labrinidis, and P. Chrysanthis. Balancing Energy Efficiency and Quality of Aggregate Data in Sensor Networks. In VLDB Jounal, 2004.
  21. S. Subramaniam, T. Palpanas, D. Papadopoulos, V. Kalogeraki, and D. Gunopulos. Online Outlier Detection in Sensor Data Using Non-Parametric Models. In VLDB, pages 187-198, 2006.
  22. Sapon Tanachaiwiwat and Ahmed Helmy. Correla tion Analysis for Alleviating Effects of Inserted Data in Wireless Sensor Networks. In IEEE International Conference on MobiQuitous, 2005.
  23. C.C. Shen, C. Srisathapornphat, and C. Jaikaeo. Sensor Information Networking Architecture and Applications. In IEEE Personal Comm., col. 8, no. 4, pp.52-59, 2001.
  24. Yannis Kotidis et al. Robust Management of Outliers in Sensor Network Aggregate Queries. In MobiDE, 2007.
  25. S. Yoon and C. Shahabi. Exploiting Spatial Correlation Towards Energy Efficient Clustered Aggregation in Sensor Networks. In Proc. of ICC, 2005.
  26. J. Zhu and S. Papavassiliou. On the Connectivity Modeling and the Tradeoffs between Reliability and Energy Efficiency in Large Scale Wireless Sensor Networks. In Proc. IEEE Wireless Comm. and Networking Conf., Vol. 2, pp. 1260-1265, 2003.
  27. L.Hu. Evans. Secure Aggregation for Wireless Networks. In Proc. of SACNT, 2003.
  28. Yi Yang et al. A Secure Hop-by-Hop Data Aggregation Protocol for Sensor Networks. In MobiHoc, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Sensor Networks Resilient aggregation Outlier detection data integrity