Cloud-Assisted Data Fusion and Sensor Selection for Internet of Things

IEEE Internet of Things Journal

Volumn 3, Issue 3, 2016, Pages 257-268

  Bijarbooneh, Farshid Hassani ^a   Du, Wei ^b   Ngai, Edith C H ^a   Fu, Xiaoming ^c   Liu, Jiangchuan ^d  

^a UPPSALA UNIVERSITY   (Sweden)

^b UNIV LYON   (France)

^c UNIVERSITY OF GÖTTINGEN   (Germany)

^d SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING; CONSTRAINT THEORY; DATA FUSION; ENERGY UTILIZATION; INFERENCE ENGINES; INTERNET; MESSAGE PASSING; NETWORK MANAGEMENT; SENSOR DATA FUSION; SENSOR NODES;

BELIEF PROPAGATION; CONSTRAINT PROGRAMMING; INTERNET OF THING (IOT); MESSAGE PASSING ALGORITHM; PREDICTION ACCURACY; REDUCE ENERGY CONSUMPTION; SENSOR SELECTION PROBLEM; SPATIOTEMPORAL CORRELATION;

INTERNET OF THINGS;

EID: 84969759650     PISSN: None     EISSN: 23274662     Source Type: Journal    
DOI: 10.1109/JIOT.2015.2502182     Document Type: Article

References (29)

1. Cisco. (2011). "The Internet of Things," [Online]. Available: http://share.cisco.com/internet-of-things.html
2. L. Atzori, A. Iera, and G. Morabito, "The Internet of Things: A survey," Comput. Netw., vol. 54, no. 15, pp. 2787-2805, Oct. 2010.
3. O. Vermesan et al., "Internet of Things strategic research roadmap," in Internet of Things-Global Technological and Societal Trends. Delft, The Netherlands: River Pub., 2011, pp. 9-52.
4. J. Amaro, F. J. T. E. Ferreira, R. Cortesao, N. Vinagre, and R. Bras, "Low cost wireless sensor network for in-field operation monitoring of induction motors," in Proc. IEEE Int. Conf. Ind. Technol. (ICIT), Mar. 2010, pp. 1044-1049.
5. S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "Tag: A tiny aggregation service for ad-hoc sensor networks," SIGOPS Oper. Syst. Rev., vol. 36, no. SI, pp. 131-146, Dec. 2002.
6. S. Madden, R. Szewczyk, M. Franklin, and D. Culler, "Supporting aggregate queries over ad-hoc wireless sensor networks," in Proc. 4th IEEE Workshop Mobile Comput. Syst. Appl., 2002, pp. 49-58.
7. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Mateo, CA, USA: Morgan Kaufmann, 1988.
8. J. S. Yedidia, W. T. Freeman, and Y. Weiss, "Understanding belief propagation and its generalizations," in Exploring Artificial Intelligence in the NewMillennium, G. Lakemeyer and B. Nebel, Eds. SanMateo, CA, USA: Morgan Kaufmann, 2003, pp. 239-269.
9. F. V. Jensen, Introduction to Bayesian Networks, 1st ed. Berlin, Germany: Springer-Verlag, 1996.
10. L. Kong, D. Jiang, and M.-Y. Wu, "Optimizing the spatio-temporal distribution of cyber-physical systems for environment abstraction," in Proc. IEEE 30th Int. Conf. Distrib. Comput. Syst. (ICDCS), Jun. 2010, pp. 179-188.
11. L. Kong, M. Xia, X.-Y. Liu, M.-Y. Wu, and X. Liu, "Data loss and reconstruction in sensor networks," in Proc. IEEE INFOCOM, 2013, pp. 1654-1662.
12. F. Rossi, P. van Beek, and T. Walsh, Eds., Handbook of Constraint Programming. Amsterdam, The Netherlands: Elsevier, 2006.
13. L. D. Xu, "Enterprise systems: State-of-The-art and future trends," IEEE Trans. Ind. Informat., vol. 7, no. 4, pp. 630-640, Nov. 2011.
14. J. Zheng, D. Simplot-Ryl, C. Bisdikian, and H. Mouftah, "The Internet of Things," IEEE Commun. Mag., vol. 49, no. 11, pp. 30-31, Nov. 2011.
15. L. Palopoli, R. Passerone, and T. Rizano, "Scalable offline optimization of industrial wireless sensor networks," IEEE Trans. Ind. Informat., vol. 7, no. 2, pp. 328-339, May 2011.
16. J. Haupt, W. Bajwa, M. Rabbat, and R. Nowak, "Compressed sensing for networked data," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008.
17. A. Ulusoy, O. Gurbuz, and A. Onat, "Wireless model-based predictive networked control system over cooperative wireless network," IEEE Trans. Ind. Informat., vol. 7, no. 1, pp. 41-51, Feb. 2011.
18. M. Jongerden, A. Mereacre, H. Bohnenkamp, B. Haverkort, and J. Katoen, "Computing optimal schedules of battery usage in embedded systems," IEEE Trans. Ind. Informat., vol. 6, no. 3, pp. 276-286, Aug. 2010.
19. O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis, "Collection tree protocol," in Proc. 7th ACM Conf. Embedded Netw. Sensor Syst., 2009, pp. 1-14.
20. S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "Tinydb: An acquisitional query processing system for sensor networks," ACM Trans. Database Syst., vol. 30, no. 1, pp. 122-173, Mar. 2005.
21. J. Chou, D. Petrovic, and K. Ramachandran, "A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks," in Proc. 22nd Annu. Joint Conf. IEEE Comput. Commun. IEEE Soc. (INFOCOM'03), 2003, vol. 2, pp. 1054-1062.
22. S. Madden. (2014). "Intel Lab data, 2004," [Online]. Available from http://www.select.cs.cmu.edu/data/labapp3/index.html
23. T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms, 3rd ed. Cambridge, MA, USA: MIT Press, 2009.
24. A. T. Ihler, J. W. Fischer III, and A. S. Willsky, "Loopy belief propagation: Convergence and effects of message errors," J. Mach. Learn. Res., vol. 6, pp. 905-936, Dec. 2005.
25. Y. Weiss and W. T. Freeman, "On the optimality of solutions of the maxproduct belief-propagation algorithm in arbitrary graphs," IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 736-744, Sep. 2006.
26. J. Su, H. Zhang, C. X. Ling, and S. Matwin, "Discriminative parameter learning for Bayesian networks," in Proc. 25th Int. Conf. Mach. Learn. (ICML'08), 2008, pp. 1016-1023.
27. A. Gersho and R.M. Gray, Vector Quantization and Signal Compression. Norwell, MA, USA: Kluwer, 1991.
28. G. Anastasi, A. Falchi, A. Passarella, M. Conti, and E. Gregori, "Performance measurements of motes sensor networks," in Proc. 7th ACM Int. Symp. Model. Anal. Simul. Wireless Mobile Syst. (MSWiM'04), 2004, pp. 174-181.
29. Gecode Team. (2006). "Gecode: A generic constraint development environment," [Online]. Available: http://www.gecode.org