Skip to main content
Log in

A Survey of Methods for Finding Outliers in Wireless Sensor Networks

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

Outlier detection is a well studied problem in various fields. The unique characteristics and constraints of wireless sensor networks (WSN) make this problem especially challenging. Sensors can detect outliers for a plethora of reasons and these reasons need to be inferred in real time. Here, we survey the current state of research in this area, compare them and present some future directions for smarter handling of outliers in WSN.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. The authors of LOF referred to k as minPts.

References

  1. Ozdemir, S., Xiao, Y.: FTDA: outlier detection-based fault-tolerant data aggregation for wireless sensor networks. Secur. Commun. Netw. 6, 702–710 (2013)

    Google Scholar 

  2. Yang, Z., Wu, C., Chen, T., Zhao, Y., Gong, W., Liu, Y.: Detecting outlier measurements based on graph rigidity for wireless sensor network localization. IEEE Trans. Veh. Technol. (TVT) 62, 374–383 (2013)

    Google Scholar 

  3. Petrovskiy, M.I.: Outlier detection algorithms in data mining systems. Program. Comput. Softw. 29(4), 228–237 (2003)

    Article  Google Scholar 

  4. Moore, D.S., McCabe, G.P.: Introduction to the Practice of Statistics, 4th ed. W. H. Freeman, San Francisco (2002)

    Google Scholar 

  5. Grubbs, F.E.: Procedures for detecting outlying observations in samples’. Technometrics 11(1), 1–21 (1969)

    Article  Google Scholar 

  6. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38, 393–422 (2002)

    Article  Google Scholar 

  7. Sheng, B., Li, Q., Mao, W., Jin, W.: Outlier detection in sensor networks. In: MobiHoc ’07: Proceedings of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing, ACM, New York, NY, USA, pp 219–228 (2007)

  8. Böhm, C., Faloutsos, C., Plant, C.: Outlier-robust clustering using independent components. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, ACM, New York, NY, USA, pp. 185–198 (2008)

  9. Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis, 1st ed. Wiley-Interscience, New York (2001)

    Book  Google Scholar 

  10. Papadimitriou, S., Kitagawa, H., Gibbons, P., Faloutsos, C.: Loci: fast outlier detection using the local correlation integral. In: Proceedings of 19th International Conference on Data Engineering, pp. 315–326 (March 2003)

  11. Branch, J., Szymanski, B., Giannella, C., Wol, R., Kargupta, H.: In-network outlier detection in wireless sensor networks. In: 26th IEEE International Conference on Distributed Computing Systems, ser. Distributed Computing Systems, pp. 51–60 (July 2006)

  12. Branch, J., Szymanski, B., Giannella, C., Wol, R., Kargupta, H.: In-network outlier detection in wireless sensor networks. Knowl. Inf. Syst. 34(1), 23–54 (2013)

    Article  Google Scholar 

  13. Dutta, H., Giannella, C., Borne, K.D., Kargupta, H.: Distributed top-k outlier detection from astronomy catalogs using the demac system. In: SDM (2007)

  14. Breunig, M.M., Kriegel, H.-P., Ng, R.T., Sander, J.: Lof: identifying density-based local outliers. In: SIGMOD Conference, pp. 93–104 (2000)

  15. Finkel, R.A., Bentley, J.L.: Quad trees: a data structure for retrieval on composite keys. Acta Inf. 4, 1–9 (1974)

    Article  MATH  Google Scholar 

  16. Subramaniam, S., Palpanas, T., Papadopoulos, D., Kalogeraki, V., Gunopulos, D.: Online outlier detection in sensor data using non-parametric models. In: VLDB’06: Proceedings of the 32nd International Conference on Very Large Data Bases. VLDB Endowment, pp. 187–198 (2006)

  17. Zhuang, Y., Chen, L.: In-network outlier cleaning for data collection in sensor networks. In: CleanDB (2006)

  18. Salvador, S., Chan, P.: Toward accurate dynamic time warping in linear time and space. Intell. Data Anal. 11(5), 561–580 (2007)

    Google Scholar 

  19. Zhang, K., Hutter, M., Jin, W.: A new local distance-based outlier detection approach for scattered real-world data. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Bao, H.T. (eds.) Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’09), Ser. LNAI., vol. 5467, pp. 813–822. Springer, Berlin (2009)

  20. Li, W., Joshi, A.: Outlier detection in ad hoc networks using Dempster–Shafer theory. In: 10th International Conference on Mobile Data Management (MDM 2009). IEEE Computer Society, pp. 112–121 (May 2009)

  21. Shafer, G.: Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  22. Giatrakos, N., Kotidis, Y., Deligiannakis, A., Vassalos, V., Theodoridis, Y.: Taco: tunable approximate computation of outliers in wireless sensor networks. In: ACM International Conference on Management of Data, Ser. SIGMOD (June 2010)

  23. Burdakis, S., Deligiannakis, A.: Detecting outliers in sensor networks using the geometric approach. In: 28th IEEE International Conference on Data Engineering, Ser. Data Engineering (April 2012)

  24. Zhang, Y., Hamm, N., Meratnia, N., Stein, A., Voort, M., Havinga, P.: Statistics-based outlier detection for wireless sensor networks. J. Geogr. Inf. Sci. 26, 1373–1392 (2012)

    Google Scholar 

  25. McDonald, D., Madria, S., Ercal, F., Birmingham, R., Lake, T.: Ctod: collaborative tree-based outlier detection in wireless sensor networks. In: MOBIWAC, ACM, IEEE Computer Society, pp. 1–10 (May 2012)

  26. Zhang, Y., Meratnia, N., Havinga, P.: Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine. J. Ad Hoc Netw. 11, 1062–1074 (May 2013)

    Google Scholar 

Download references

Acknowledgments

This research is partially supported by a grant from DOE, P200A070359. Thanks to Vimal Kumar for providing help in revising this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sanjay Madria.

Rights and permissions

Reprints and permissions

About this article

Cite this article

McDonald, D., Sanchez, S., Madria, S. et al. A Survey of Methods for Finding Outliers in Wireless Sensor Networks. J Netw Syst Manage 23, 163–182 (2015). https://doi.org/10.1007/s10922-013-9287-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10922-013-9287-z

Keywords

Navigation