Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A Hierarchical Bitmap-based Spatial Index use k-Nearest Neighbor Query Processing on the Wireless Broadcast Environment

무선방송환경에서 계층적 비트맵 기반 공간 색인을 이용한 k-최근접 질의처리

  • Song, Doo-Hee (Dept. of Information and Communication, Wonkwang University) ;
  • Park, Kwang-Jin (Dept. of Information and Communication, Wonkwang University)
  • 송두희 (원광대학교 정보통신학과) ;
  • 박광진 (원광대학교 정보통신학과)
  • Received : 2011.10.07
  • Accepted : 2011.10.24
  • Published : 2012.01.31
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Abstract

Recently, k-nearest neighbors query methods based on wireless broadcasting environment are actively studied. The advantage of wireless broadcasting environment is the scalability that enables collective query processing for unspecified users connected to the server. However, in case existing k-NN query is applied in wireless broadcasting environment, there can be a disadvantage that backtracking may occur and consequently the query processing time is increasing. In this paper proposes a hierarchical bitmap-based spatial index in order to efficiently process the k-NN queries in wireless broadcasting environment. HBI reduces the bitmap size using such bitmap information and tree structure. As a result, reducing the broadcast cycle can reduce the client's tuning time and query processing time. In addition, since the locations of all the objects can be detected using bitmap information, it is possible to tune to necessary data selectively. For this paper, a test was conducted implementing HBI to k-NN query and the proposed technique was proved to be excellent by a performance evaluation.

최근 무선방송 환경을 기반으로 하는 k-최근접(k-Nearest Neighbor) 질의처리가 활발히 연구되고 있다. 무선방송환경의 장점은 서버 내에 존재하는 불특정 다수에게 일괄적으로 질의처리를 할 수 있는 확장성을 가진다는 것이다. 그러나 기존의 k-NN 질의는 무선방송환경에 적용할 경우 탐색과정에서 백트래킹이 발생하여 질의처리시간이 증가하는 단점을 가진다. 본 논문은 무선방송환경에서 k-NN 질의를 효과적으로 처리하기 위하여 계층적 비트맵 기반 공간색인(Hierarchical Bitmap-based Spatial Index: HBI)을 제안한다. HBI는 비트맵 정보와 트리 구조를 이용하여 비트맵의 크기를 줄인다. 결과적으로 방송주기를 줄임으로써 클라이언트의 청취시간과 질의처리 시간을 줄일 수 있다. 또한 비트맵 정보를 활용하여 객체의 위치를 모두 파악할 수 있기 때문에 필요한 데이터를 선택적으로 청취할 수 있다. 본 논문에서는 HBI를 k-NN 질의에 적용하여 실험을 실시하고 성능평가에서 제안 기법이 우수함을 증명한다.

Keywords

References

  1. M.-S. Chen, K.-L. Wu, and P.S. Yu, "Optimizing Index Allocation for Sequential Data Broadcasting in Wireless Mobile Computing", IEEE Trans. Knowledge and Data Eng., vol 15, no. 1, pp. 161-173, Jan./Feb. 2003. https://doi.org/10.1109/TKDE.2003.1161588
  2. K. Park, H. Choo, and V. Patrick, "A scalable energy-efficient continuous nearest neighbor search in wireless broadcast systems", Wireless Networks vol. 16, no. 4, pp. 1011-1031, May 2010. https://doi.org/10.1007/s11276-009-0185-y
  3. D. Song and K. Park, "An Efficient Bitmap-based Selective Tuning Scheme for Spatial Queries in Location-based Service", In Proc. of Intl. Conf. on Internet, pp. 503-509, Mac tan Island, Philippines, Dec. 2010.
  4. J. Yim, K. Lee and S. Jeong, "Experimental Data Collection for Moving Pattern Information Extraction in Location based Service", Korea Society of Computer Information, vol. 16, no. 1, pp. 17-24, June 2008.
  5. J. Song, D. Kim and J. Lee, "Region-Based Image Retrieval System using Spatial Location Information as Weights for Relevance Feedback", Korea Society of Computer Information, vol. 11, no. 4, pp. 1-7, Sep. 2006.
  6. P. Bellavista, A. Kupper, and S. Helal, "Location-based Services: Back to the Future", IEEE Pervasive Computing vol. 7, no. 2, pp. 85-89, April/June 2008.
  7. B. Gedik, A. Singh and L. Liu, "Energy Efficient Exact kNN Search in Wireless Broadcast Environments", 12th ACM International Workshop on Geographic Information, New York, USA, pp. 137-146, June 2004.
  8. A. Guttman, "R-Trees: A Dynamic Index Structure for Spatial Searching", ACM SIGMOD Record, vol. 14, no. 2, pp. 47-57, June 1984. https://doi.org/10.1145/971697.602266
  9. B. Zheng, W. C. Lee, and D. L. Lee, "Spatial Queries in Wireless Broadcast Systems", Wireless Networks, vol. 10, no. 6, pp. 723-736, Nov. 2004. https://doi.org/10.1023/B:WINE.0000044031.03597.97
  10. P. O'Neil and G. Graefe. "Multi-Table Joins Through Bitmapped Join Indices", ACM SIGMOD Record, vol. 24, no. 3, pp. 8-11, Sep. 1995. https://doi.org/10.1145/211990.212001
  11. C. -Y. Chan, Y. E. Ioannidis, "Bitmap Index Design and Evaluation", ACM SIGMOD Record, vol. 27, no. 2, June 1998.
  12. T. Imielinski, S. Viswanathan, and B. R. Badrinath, "Data on Air: Organization and Access", IEEE Transactions on Knowledge and Data Engineering, vol. 9, no. 3, pp. 353-372, May 1997. https://doi.org/10.1109/69.599926
  13. C. Gotsman and M. Lindenbaum. "On the Metric Properties of Discrete Space-Filling Curves", IEEE Transactions on Image Processing, vol. 5, no. 5, pp. 794-797, May 1996. https://doi.org/10.1109/83.499920
  14. B. Zheng, W. -C. Lee, Ken C. K. Lee, D. L. Lee, and M. Shao, "A Distributed spatial index for Error-Prone wireless Data broadcast", Very Large Data Bases Journal, vol. 18, no. 4, pp. 959-986, Aug. 2009. https://doi.org/10.1007/s00778-009-0137-2
  15. H. Sin, M. Lee, J. Choi and S. Lee, "Bitmap-based Spatial Index on Wireless Broadcast Environments", SIGDB-KISS, vol. 23, no. 1, pp. 23-36, April 2007.

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