본문 바로가기
KERD
논문KCI 등재

과거 위치 색인에서 입력/검색 비용 조정을 위한 가변 버퍼 노드 기법 설계

Design of the Flexible Buffer Node Technique to Adjust the Insertion/Search Cost in Historical Index

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류공학

초록

Various applications of LBS (Location Based Services) are being developed to provide the customized service depending on user's location with progress of wireless communication technology and miniaturization of personalized device. To effectively process an amount of vehicles' location data, LBS requires the techniques such as vehicle observation, data communication, data insertion and search, and user query processing. In this paper, we propose the historical location index, GIP-FB (Group Insertion tree with Flexible Buffer Node) and the flexible buffer node technique to adjust the cost of data insertion and search. the designed GIP+ based index employs the buffer node and the projection storage to cut the cost of insertion and search. Besides, it adjusts the cost of insertion and search by changing the number of line segments of the buffer node with user defined time interval. In the experiment, the buffer node size influences the performance of GIP-FB by changing the number of non-leaf node of the index. the proposed flexible buffer node is used to adjust the performance of the historical location index depending on the applications of LBS.

Abstract

Various applications of LBS (Location Based Services) are being developed to provide the customized service depending on user's location with progress of wireless communication technology and miniaturization of personalized device. To effectively process an amount of vehicles' location data, LBS requires the techniques such as vehicle observation, data communication, data insertion and search, and user query processing. In this paper, we propose the historical location index, GIP-FB (Group Insertion tree with Flexible Buffer Node) and the flexible buffer node technique to adjust the cost of data insertion and search. the designed GIP+ based index employs the buffer node and the projection storage to cut the cost of insertion and search. Besides, it adjusts the cost of insertion and search by changing the number of line segments of the buffer node with user defined time interval. In the experiment, the buffer node size influences the performance of GIP-FB by changing the number of non-leaf node of the index. the proposed flexible buffer node is used to adjust the performance of the historical location index depending on the applications of LBS.

참고문헌 (27)

  1. Y. J. Jung, "Historical Index Structure for reducing Insertion and Search Cost in LBS", The Journal of systems and software, 83(1), pp.1500~1511 (2000)
  2. J. H. Reed, "An Overview of the Challenges and Progress in Meeting the E-911 Requirement for Location Service", IEEE Communication Magazine, pp.33~37 (1998)
  3. O. Wolfson, "Moving Objects Databases: Issues and Solutions", SSDBM, pp.111~112 (1998)
  4. L. Forlizzi, "A Data Model and Data Structures for Moving Objects Databases", ACM SIGMOD, pp.319~330 (2000)
  5. A. Guttman, "A.:R-trees: a Dynamic Index Structure for Spatial Searching", ACM-SIGMOD, pp.47~57 (1984)
  6. J. H. Reed, "An Overview of the Challenges and Progress in Meeting the E-911 Requirement for Location Service", IEEE Communication Magazine, pp.33~37 (1998)
  7. M. F. Mokbel, "Spatio-temporal Access Methods", IEEE Data Engineering Bulletin, 36(2), pp.40~49 (2003)
  8. K. U, Kalipsiz O, "A comparison study of moving object index structures", Journal of Computer Science and Technology, 24(6), pp.1098~1108 (2009)
  9. C. S. Jensen, "Query and Update Efficient B+tree based Indexing of Moving Objects", 30th International Conference on Very Large Data Bases (VLDB), pp.768~779 (2004)
  10. D.Lin, "Indexing and Querying Moving Objects Databases", 박사, pp.2006
  11. C. S. Jensen, "Robust B+-Tree-Based Indexing of Moving Objects", Seventh International Conference on Mobile Data Management, pp.12~ (2006)
  12. S. Chen, "ST2B-tree: A Self-Tunable Spatio-Temporal B+-tree for Moving Objects", ACM SIGMOD International Conference on Management of Data (SIGMOD), pp.29~42 (2008)
  13. M. Zhang, "Effectively Indexing Uncertain Moving Objects for Predictive Queries", 35th International Conference on Very Large Data Bases (VLDB), 1(1), pp.1198~1209 (2009)
  14. S. Chen, "A Benchmark for Evaluating Moving Objects Indexes", 34th International Conference on Very Large Data Bases (VLDB), pp.1574~1585 (2008)
  15. Indexing Trajectories of Moving Point Objects, "D. Pfoser", CHOROCHRONOS TECHNICAL, ~, pp.CH-99-03 (1999)
  16. Novel Approaches in Query Processing for Moving Objects, "D. Pfoser", CHOROCHRONOS TECHNICAL, ~, pp.CH-00-03 (2000)
  17. Y. J. Jung, "MP-tree : An Index Approach for Moving Objects in Mobile Environment", ASGIS, pp.104~111 (2003)
  18. C. S. Jensen, "Query and Update Efficient B+-Tree Based Indexing of Moving Objects", VLDB, pp.768~779 (2004)
  19. Samet, H, "The Design and Analysis of Spatial Data Structures", pp.47~ (1990), Addison-Wesley
  20. S. Saltenis, "Indexing the Positions of Continuously Moving Objects", ACM-SIGMOD, pp.331~342 (2000)
  21. D. S. Kwon, "Indexing the Current Positions of Moving Objects Using the Lazy Update R-Tree", Mobile Data Management, pp.113~120 (2002)
  22. M. L. Lee, "Supporting Frequent Updates in R-Trees: A Bottom-Up Approach", VLDB, pp.608~619 (2003)
  23. Y. Tao, "The TPR*-tree: an optimized spatio-temporal access method for predictive queries", VLDB, pp.790~801 (2003)
  24. L. Chen, "Bulk Insertions into R-trees using the Small-Tree-Large-Tree Approach", Procedings of ACM GIS Workshop, pp.161~162 (1998)
  25. G. R. Hjaltason, "Speeding up construction of PMR quadtree-based spatial indexes", VLDB Journal, 11(2), pp.109~137 (2002)
  26. N. An, "Improving performance with bulk-inserts in Oracle R-trees", the 29th VLDB, pp.948~951 (2003)
  27. 정영진, "차량 위치 정보 저장을 위한 버퍼 노드 기반 그룹 갱신 기법", 정보과학회논문지 : 데이타베이스, 33(1), pp.1~11 (2006), 한국정보과학회

관련 논문AI추천

이 간행물의 다른 논문 (8건)