The Computer Journal - Special issue on parallel computing
Overlapping B+trees for temporal data
JCIT Proceedings of the fifth Jerusalem conference on Information technology
Multidimensional access methods
ACM Computing Surveys (CSUR)
Overlapping linear quadtrees: a spatio-temporal access method
Proceedings of the 6th ACM international symposium on Advances in geographic information systems
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
SAC '98 Proceedings of the 1998 ACM symposium on Applied Computing
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A data model and data structures for moving objects databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Using space-time grid for efficient management of moving objects
Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
Survey of Spatio-Temporal Databases
Geoinformatica
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Specifications for Efficient Indexing in Spatiotemporal Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
On the Generation of Spatiotemporal Datasets
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
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
An asymptotically optimal multiversion B-tree
The VLDB Journal — The International Journal on Very Large Data Bases
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Spatio-temporal data warehouses using an adaptive cell-based approach
Data & Knowledge Engineering
Geosensor Data Abstraction for Environmental Monitoring Application
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
A cost model for an adaptive cell-based index structure
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
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R-tree based access methods for moving objects are hardly applicable in practice, due mainly to excessive space requirements and high management costs. To overcome the limitations of such R-tree based access methods, we propose a new index structure called AIM (Adaptive cell-based Index for Moving objects). The AIM is a cell-based multiversion access structure adopting an overlapping technique. The AIM refines cells adaptively to handle regional data skew, which may change its locations over time. Through the extensive performance studies, we observed that The AIM consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with R-tree based methods.