Online fusion of incremental learning for Wireless Sensor Networks

IEEE International Conference on Data Mining Workshops, ICDMW

Volumn 2015-January, Issue January, 2015, Pages 525-532

  Bosman, H H W J ^a   Iacca, G ^a   Wortche, H J ^b   Liotta, A ^b  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b INCAS ^*  (Netherlands)

Author keywords

Anomaly detection; Embedded Systems; Online Learning

Indexed keywords

DATA MINING; E-LEARNING; EMBEDDED SYSTEMS; FORECASTING; HEURISTIC METHODS; ONLINE SYSTEMS; TIME SERIES; WIRELESS SENSOR NETWORKS;

DISTRIBUTED EMBEDDED SYSTEM; ENSEMBLE OF CLASSIFIERS; GENERAL STATISTICS; INCREMENTAL LEARNING; INDIVIDUAL CLASSIFIERS; LARGE AMOUNTS OF DATA; ONLINE ANOMALY DETECTION; ONLINE LEARNING;

ANOMALY DETECTION;

EID: 84936864916     PISSN: 23759232     EISSN: 23759259     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2014.79     Document Type: Conference Paper

References (30)

1. A. Liotta, "The cognitive net is coming, " IEEE Spectrum, vol. 50, no. 8, pp. 26-31, August 2013.
2. S. Galzarano, G. Fortino, and A. Liotta, "A learning-based mac for energy efficient wireless sensor networks, " in Proc. of the 7th International Conference on Internet and Distributed Computing Systems. Springer, LNCS, September 2014.
3. L. Bencini, F. Chiti, G. Collodi, D. Di Palma, R. Fantacci, A. Manes, and G. Manes, "Agricultural monitoring based on wireless sensor network technology: real long life deployments for physiology and pathogens control, " in Sensor Technologies and Applications, 2009. SENSORCOMM'09. Third International Conference on. IEEE, 2009, pp. 372-377.
4. K. Martinez, J. K. Hart, and R. Ong, "Deploying a wireless sensor network in Iceland, " in GeoSensor Networks. Springer, 2009, pp. 131-137.
5. J. A kerberg, M. Gidlund, T. Lennvall, J. Neander, and M. Bjrkman, "Efficient integration of secure and safety critical industrial wireless sensor networks, " EURASIP Journal on Wireless Communications and Networking, vol. 2011, no. 1, pp. 1-13, 2011.
6. R. Jurdak, X. Wang, O. Obst, and P. Valencia, "Wireless sensor network anomalies: Diagnosis and detection strategies, " Intelligence-Based Systems Engineering, pp. 309-325, 2011.
7. E. Fuchs, T. Gruber, J. Nitschke, and B. Sick, "Online segmentation of time series based on polynomial least-squares approximations, " Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 32, no. 12, pp. 2232-2245, 2010.
8. H. H. W. J. Bosman, A. Liotta, G. Iacca, and H. J. Wortche, "Anomaly detection in sensor systems using lightweight machine learning, " in Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on. IEEE, 2013, pp. 7-13.
9. K. Ni, N. Ramanathan, M. Chehade, L. Balzano, S. Nair, S. Zahedi, E. Kohler, G. Pottie, M. Hansen, and M. Srivastava, "Sensor network data fault types, " ACM Transactions on Sensor Networks, vol. 5, no. 3, p. 25, 2009.
10. A. B. Sharma, L. Golubchik, and R. Govindan, "Sensor faults: Detection methods and prevalence in real-world datasets, " ACM Transactions on Sensor Networks, vol. 6, no. 3, 2010.
11. Y. Yao, A. Sharma, L. Golubchik, and R. Govindan, "Online anomaly detection for sensor systems: A simple and efficient approach, " Performance Evaluation, 2010.
12. R. Biuk-Aghai, Y.-W. Si, S. Fong, and P.-F. Yan, "Individual movement behaviour in secure physical environments: Modeling and detection of suspicious activity, " in Behavior Computing, L. Cao and P. S. Yu, Eds. Springer London, 2012, pp. 241-253.
13. C. Phua, V. Lee, K. Smith, and R. Gayler, "A comprehensive survey of data mining-based fraud detection research, " Arxiv preprint arXiv:1009.6119, 2010.
14. S. Kao, A. Ganguly, and K. Steinhaeuser, "Motivating complex dependence structures in data mining: A case study with anomaly detection in climate, " in 2009 IEEE International Conference on Data Mining Workshops. IEEE, 2009, pp. 223-230.
15. C. Wang, K. Viswanathan, L. Choudur, V. Talwar, W. Satterfield, and K. Schwan, "Statistical techniques for online anomaly detection in data centers, " in Integrated Network Management (IM), 2011 IFIP/IEEE International Symposium on. IEEE, 2011, pp. 385-392.
16. Y. Zhang, N. Meratnia, and P. Havinga, "Outlier detection techniques for wireless sensor networks: A survey, " Communications Surveys & Tutorials, IEEE, vol. 12, no. 2, pp. 159-170, 2010.
17. M. Xie, S. Han, B. Tian, and S. Parvin, "Anomaly detection in wireless sensor networks: A survey, " Journal of Network and Computer Applications, 2011.
18. M. Chang, A. Terzis, and P. Bonnet, "Mote-based online anomaly detection using echo state networks, " in Distributed Computing in Sensor Systems. Springer, 2009, pp. 72-86.
19. F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler, and H. Efendic, "Fault detection in multi-sensor networks based on multivariate time-series models and orthogonal transformations, " Information Fusion, 2014.
20. L. Ljung and S. Gunnarsson, "Adaptation and tracking in system identification- A survey, " Automatica, vol. 26, no. 1, pp. 7-21, 1990.
21. C. Lo, J. Lynch, and M. Liu, "Reference-free detection of spike faults in wireless sensor networks, " in Resilient Control Systems (ISRCS), 2011 4th International Symposium on. IEEE, 2011, pp. 148-153.
22. F. L. Bookstein, "On a form of piecewise linear regression, " The American Statistician, vol. 29, no. 3, pp. 116-117, 1975.
23. L. K. Hansen and P. Salamon, "Neural network ensembles, " IEEE transactions on pattern analysis and machine intelligence, vol. 12, pp. 993-1001, 1990.
24. D.-I. Curiac and C. Volosencu, "Ensemble based sensing anomaly detection in wireless sensor networks, " Expert Systems with Applications, vol. 39, no. 10, pp. 9087-9096, 2012.
25. H. H. W. J. Bosman, A. Liotta, G. Iacca, and H. J. Wortche, "Online extreme learning on fixed-point sensor networks, " in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on. IEEE, 2013, pp. 319-326.
26. R. A. Fisher, Statistical methods for research workers. Genesis Publishing Pvt Ltd, 1925.
27. P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer et al., "Tinyos: An operating system for sensor networks, " in Ambient intelligence. Springer, 2005, pp. 115-148.
28. E. Fuchs, T. Hanning, O. Schwarz, T. Gruber, J. Nitschke, and B. Sick, "Fast function approximation library." http://www.ies-research.de/Software
29. P. Levis, N. Lee, M. Welsh, and D. Culler, "Tossim: Accurate and scalable simulation of entire tinyos applications, " in Proceedings of the 1st international conference on Embedded networked sensor systems. ACM, 2003, pp. 126-137.
30. J. Eriksson, A. Dunkels, N. Finne, F. sterlind, and T. Voigt, "MSPsim-an Extensible Simulator for MSP430-equipped Sensor Boards, " in Proceedings of the European Conference on Wireless Sensor Networks (EWSN), Poster/Demo session, jan 2007.