Query and Update Efficient B+-Tree Based Indexing of Moving Objects

Christian Søndergaard Jensen, Dan Lin, Beng Chin Ooi

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearch


A number of emerging applications of data management technology involve the monitoring and querying of large quantities of continuous variables, e.g., the positions of mobile service users, termed moving objects. In such applications, large quantities of state samples obtained via sensors are streamed to a database. Indexes for moving objects must support queries efficiently, but must also support frequent updates. Indexes based on minimum bounding regions (MBRs) such as the R-tree exhibit high concurrency overheads during node splitting, and each individual update is known to be quite costly. This motivates the design of a solution that enables the B+-tree to manage moving objects. We represent moving-object locations as vectors that are timestamped based on their update time. By applying a novel linearization technique to these values, it is possible to index the resulting values using a single B+-tree that partitions values according to their timestamp and otherwise preserves spatial proximity. We develop algorithms for range and k nearest neighbor queries, as well as continuous queries. The proposal can be grafted into existing database systems cost effectively. An extensive experimental study explores the performance characteristics of the proposal and also shows that it is capable of substantially outperforming the R-tree based TPR-tree for both single and concurrent access scenarios.
Original languageEnglish
Title of host publicationProceedings of the Thirtieth International Conference on Very Large Data Bases
Number of pages12
Publication date2004
Publication statusPublished - 2004
EventVLDB 2004 - Toronto, Canada
Duration: 9 Aug 20043 Sep 2004
Conference number: 30


ConferenceVLDB 2004


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