PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On two-dimensional indexability and optimal range search indexing
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data structures for mobile data
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Kinetic binary space partitions for intersecting segments and disjoint triangles
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Database Management Systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Indexing the Current Positions of Moving Objects Using the Lazy Update R-tree
MDM '02 Proceedings of the Third International Conference on Mobile Data Management
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Indexing continuously changing data with mean-variance tree
Proceedings of the 2005 ACM symposium on Applied computing
The Indiana Center for Database Systems at Purdue University
ACM SIGMOD Record
Quality-Aware Probing of Uncertain Data with Resource Constraints
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Indexing continuously changing data with mean-variance tree
International Journal of High Performance Computing and Networking
The RUM-tree: supporting frequent updates in R-trees using memos
The VLDB Journal — The International Journal on Very Large Data Bases
Data management challenges for computational transportation
Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
Update-efficient indexing of moving objects in road networks
Geoinformatica
The VLDB Journal — The International Journal on Very Large Data Bases
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Workload-aware indexing of continuously moving objects
Proceedings of the VLDB Endowment
Load balancing for moving object management in a P2P network
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Bulkloading updates for moving objects
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
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Index structures are designed to optimize search performance, while at the same time supporting efficient data updates. Although not explicit, existing index structures are typically based upon the assumption that the rate of updates will be small compared to the rate of querying. This assumption is not valid in streaming data environments such as sensor and moving object databases, where updates are received incessantly. In fact, for many applications, the rate of updates may well exceed the rate of querying. In such environments, index structures suffer from poor performance due to the large overhead of keeping the index updated with the latest data. Recent efforts at indexing moving object data assume objects move in a restrictive manner (e.g. in straight lines with constant velocity). In this paper, we propose an index structure explicitly designed to perform well for both querying and updating. We assume a more relaxed model of object movement. In particular, we observe that objects often stay in a region (e.g., building) for an extended amount of time, and exploit this phenomenon to optimize an index for both updates and queries. The paper is developed with the example of R-trees, but the ideas can be extended to other index structures as well. We present the design of the Change Tolerant R-tree, and an experimental evaluation.