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An Efficient Complex Event Detection Algorithm based on NFA_HTS for Massive RFID Event Stream

  • Wang, Jianhua (College of Electronic Engineering, South China Agricultural University) ;
  • Liu, Jun (College of Automation, Guangdong Polytechnic Norma University) ;
  • Lan, Yubin (National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology) ;
  • Cheng, Lianglun (College of Automation, Guangdong University of Technology)
  • Received : 2016.10.18
  • Accepted : 2017.11.15
  • Published : 2018.03.01

Abstract

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. Virgilio R D, Milicchio F. Physical design for distributed RFID-based supply chain management. DISTRIB PARALLEL DA, vol. 34, no. 1, pp. 3-32, 2016. https://doi.org/10.1007/s10619-015-7178-x
  2. Piramuthu S, Zhou W. 5. RFID in food supply-chain management. RFID and Sensor Network Automation in the Food Industry: Ensuring Quality and Safety through Supply Chain Visibility. John Wiley & Sons, Ltd, 2016.
  3. Zhai C, Zou Z, Chen Q, et al. Delay-Aware and Reliability-Aware Contention-Free MF-TDMA Protocol for Automated RFID Monitoring in Industrial IoT. Journal of Industrial Information Integration, vol. 3, pp. 8-19, 2016. https://doi.org/10.1016/j.jii.2016.06.002
  4. Ding K, Jiang P, Su S. RFID-enabled social manufacturing system for inter-enterprise monitoring and dispatching of integrated production and transportation tasks. ROBOT CIM-INT MANU, vol. 49, pp. 120-133, 2018. https://doi.org/10.1016/j.rcim.2017.06.009
  5. Del G, Eugene W, Hee J, et.al. "SASE: Complex Event Proeessing over Streams," In 3rd Biennial Conference on Innovative Data Systems Researeh. pp. 407-411, 2007.
  6. Demers A, Gehlke J, Panda B, etal. "Cayuga:A General Purpose Event Monitoring System. Comell University," In Proe of 3rd Biennial Conference on Innovative Data Systems Research, Asilomar, USA, pp. 412-422, 2007.
  7. Esper Introduction. http://esper.codehaus.org
  8. Garg V. "Estream: an Integration of Event and Stream Proeessing," Master Thesis, University of Texasat Arlington, 2005.
  9. Cybenko G, Berk H. "Proeess Query System," IEEE Computer. vol. 40, no. l, pp. 62-70, 2007.
  10. Wang F, Liu S, Liu P. "Bridging physical and virtual worlds: complex event processing for RFID data streams," LNCS 3896: the 10th International Conference on EDBT. March. pp. 588- 607, 2006.
  11. Bai L, Lao S, Smeaton A F, et al. "Semantic analysis of field sports video using apetrinet of audio-visual concepts," Computer, vol. 52, no. 7, pp. 808-823, 2009
  12. Sun X W, Chen R, Du Z J. "Composite Event Detection Based on Automata", in proc of 2009 IEEE International Conference on Intelligent Human-Machine Systems and Cybernetics. Hangzhou, China, pp. 160-163, Aug, 2009.
  13. Mei Y, Madden S. "ZStream: A cost-based query processor for adaptively detecting composite events", in Proceedings of the SIGMOD2009, USA, pp. 193-206, July, 2009.
  14. Jin X, Lee X, Kong N. "Efficient complex event processing over RFID data stream", in proceedings of the Seventh IEEE/ACIS International Conferenceon, Portland, pp. 75-81, May, 2008.
  15. Wang F, Liu S, Liu P. "Bridging physical and virtual worlds:complex event processing for RFID data streams," In proceedings of the 10th International Conference on Extending Database Technology, EDBT' Munich, Germany, pp. 588-607, March, 2006.
  16. Li Y, Wang J, Feng L. "Accelerating sequence event detection through condensed composition," Proceedings of the 5th International Conferenceon Ubiquitous Information Technologies & Applications. Sanya, pp. 6-10, 2010.
  17. Cao J, Wei X, Liu Y Q, et al. "LogCEP-Complex event processing based on pushdown automaton," International Journal of Hybrid Information Technology. vol. 7, no. 6, pp. 71-82, 2014. https://doi.org/10.14257/ijhit.2014.7.6.06
  18. Eugene W, Yanlei D, Shariq R. "High-performance Complex Event Proeessing over Streams," In proe of the SIGMOD conf. Chicago, USA, pp. 407-418, June, 2006,
  19. Zhang X L, Wang Y H, Zhang X M. "Complex Event Processing over Distributed Uncertain Event Streams," International Conference on Computer Science and Service System. pp. 357-361, july, 2014.
  20. Kyoung S B, Myung H Y, Byoung Y L, et al. "Efficient Complex Event Processing over RFID Streams," INT J DISTRIB SENS N. vol. 2012, pp. 1-9, 2012.
  21. Wang J H, Cheng L L, Liu J." A Complex Event Detection Method for Multi-probability RFID Event Stream," Journal of Software. vol. 9, nol.24, pp. 834-840, ( 2014).
  22. Peng S L; Liu H X, Guo X L, et al. "State-based event detection optimization for Complex Event Processing," Sensors and Transducers, vol. 164, nol.2, pp. 242-248, 2014.
  23. Wang, Y. H., Cao, K., Zhang, X. M., "Complex event processing over distributed probabilistic event streams," Computers and Mathematics with Applications, vol. 66 no. 10, pp. 1808-1821, 2013. https://doi.org/10.1016/j.camwa.2013.06.032
  24. Peng S L, Li Z H, Cheng, et al. "Complex event processing over live archived data streams," journal of computers, vol. 35, no. 3, pp. 540-554, 2012.
  25. M. Moon, S. Kim, K. Yeom, and H. Choi, "Framework for extending RFID events with business rule, " in Proceedings of the International Conference on Database Systems for Advanced Applications, pp. 955-961, 2007.
  26. H. Kawashima, H. Kitagawa, and X. Li, "Complex event processing over uncertain data streams," in Proceedings of the International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp. 521-526, 2010.
  27. Y. Liu and D. Wang, "Complex event processing engine for large volume of RFID data," in Proceedings of the 2nd Inter-national Workshop on Education Technology and Computer Science, pp. 429-432, March, 2010.
  28. Xiao F, Zhan C, Lai H, et al. New parallel processing strategies in complex event processing systems with data streams. International Journal of Distributed Sensor Networks, vol. 13, no. 8, 2017.
  29. Yuan L, Xu D, Ge G, et al. Study on distributed complex event processing in Internet of Things based on query plan. IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems. IEEE, pp. 666-670, 2015.
  30. Xiao F. An Intelligent Complex Event Processing with D Numbers under Fuzzy Environment. Mathematical Problems in Engineering, vol. 2016, no. 1, pp. 1-10, 2016.
  31. Abbasnejad I, Sridharan S, Denman S, et al. Complex Event Detection Using Joint Max Margin and Semantic Features. International Conference on Digital Image Computing: Techniques and Applications. IEEE, pp. 1-8, 2016.
  32. Z Tian, S Li, Y Wang, X Wang. A network traffic hybrid prediction model optimized by improved harmony search algorithm. Neural Network World, vol. 25, no. 6, pp. 669-686, 2015. https://doi.org/10.14311/NNW.2015.25.034
  33. ZD Tian, XW Gao, BL Gong, T Shi. Time-delay compensation method for networked control system based on time-delay prediction and implicit PIGPC. International Journal of Automation and Computing, vol. 12, no. 6, pp. 648-656, 2015. https://doi.org/10.1007/s11633-015-0897-7
  34. ZD Tian, SJ Li, YH Wang, HX Yu .Networked Control System Time-Delay Compensation Based on Time-Delay Prediction and Improved Implicit GPC. Algorithms, vol. 8, no. 1, pp. 3-18, 2015. https://doi.org/10.3390/a8010003
  35. Z Tian, X Gao, P Guo. Network Teleoperation Robot System Control based on Fuzzy Sliding Mode, Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 20, no. 5, pp. 828-835, 2016. https://doi.org/10.20965/jaciii.2016.p0828
  36. Diao, Y., Altinel, M., Zhang, H., Franklin, M.J., and Fischer, P.M. Path sharing and predicate evaluation for high-performance XML filtering. TODS, vol. 28, pp. 4, pp. 467-516, Dec. 2003. https://doi.org/10.1145/958942.958947
  37. H. Zhang, Y. Diao, and N. Immerman, "On complexity and optimization of expensive queries in complex event processing," in Proc. ACM SIGMOD, Snowbird, UT, USA, pp. 217-228, 2014.