Efficient Processing of Multidimensional Sensor stream Data in Digital Marine Vessel

디지털 선박 내 다차원 센서 스트림 데이터의 효율적인 처리

  • 송병호 (목포대학교 중점연구소) ;
  • 박경우 (목포대학교 컴퓨터공학과) ;
  • 이진석 (정보통신산업진흥원) ;
  • 이경효 (목포대학교 정보보호학과) ;
  • 정민아 (목포대학교 컴퓨터공학과) ;
  • 이성로 (목포대학교 정보전자공학과)
  • Received : 2010.03.08
  • Accepted : 2010.05.10
  • Published : 2010.05.31

Abstract

It is necessary to accurate and efficient management for measured digital data from various sensors in digital marine vessel. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. In this paper, We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose that we arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using SVM algorithm. We automatically delete that it isn't necessary to the data from the database and we used to ship diagnosis system for available data. As a result, we obtained to efficient result about 18.3% reduction rate of database using 35,912 data sets.

Acknowledgement

Supported by : 한국연구재단, 목포대학교

References

  1. 김재양, 정선태, 임준석, 박종원, 홍기용, 임용곤, "디지털 선박을 위한 선박 통합화 네트워크 설계 및 구현", 한국해양정보통신학회논문지, 제9권, 제6호, pp.1202-1210, 2005.10.
  2. R. Motwani, J. Widom, A. Arasu, B. Bobcock, S. Babu, M. Datar, G. Manku, C. Olston, J.Rosenstein, and R. Varma, "Query Processing, Resource Management, and Approximation in a Data Stream Management System," In Proc. of Conf. on Innovative Data Systems Research, Asilomar, CA, USA, Jan., 2003
  3. S. D. Viglas, J. F. Naughton, and J. Burger, "Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources," In Proc. 29th VLDB Conf., pp.285- 296, 2003.
  4. T. Urhan and M. J. Franklin., "XJoin: A reactivelyscheduled pipelined join operator," IEEE Data Engineering Bulletin, Vol.23, No.2, pp.27-33, 2000.
  5. L. Golab and M. T. Ozsu, "Issues in Data Stream Management," SIGMOD Record, Vol.32, No.2, June, 2003.
  6. B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom, "Models and Issues in Data Stream Systems," In Proc. of ACM SIGACT -SIGMOD-SIGART Sym. on Principles of Database Systems, pp.1-16, Wisconsin, USA, June, 2002.
  7. Ahmed M. Ayad, Jeffrey F. Naughton, "Static Optimization of Conjunctive Queries with Sliding Windows Over Infinite Streams", In Proceedings of the 2004 ACM SIGMOD, pp.419-430, 2004.
  8. Stratis D. Viglas, Jeffrey F. Naughton, "Rate-Based Query Optimization for Streaming Information Sources", In Proceedings of the 2002 ACM SIGMOD, pp.37-48, 2002.
  9. Y. Liu, R. Wang, H. Huang, Y. Zeng, and H. He, "Applying support vector machine to P2P traffic identification with smooth processing," IEEE Int. Conf. on Signal Processing, Vol.3, pp.16-20, 2006.
  10. Zhuang, D., Zhang, B., Yang, Q., Yan, J., Chen, Z., & Chen, Y. 2005. "Efficient Text Classification by Weighted Proximal SVM." Proceedings of the Fifth IEEE International Conference on Data Mining: 538-545.