The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Shoring up persistent applications
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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ACM Transactions on Database Systems (TODS)
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
An effective way to represent quadtrees
Communications of the ACM
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
IEEE Transactions on Computers
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IEEE Transactions on Knowledge and Data Engineering
Locating Objects in Mobile Computing
IEEE Transactions on Knowledge and Data Engineering
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
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The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th 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
STAR-Tree: An Efficient Self-Adjusting Index for Moving Objects
ALENEX '02 Revised Papers from the 4th International Workshop on Algorithm Engineering and Experiments
Querying Mobile Objects in Spatio-Temporal Databases
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal 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
SEB-tree: An Approach to Index Continuously Moving Objects
MDM '03 Proceedings of the 4th International Conference on Mobile Data Management
Speeding up construction of PMR quadtree-based spatial indexes
The VLDB Journal — The International Journal on Very Large Data Bases
Indexing Spatio-Temporal Data Warehouses
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Supporting frequent updates in R-trees: a bottom-up approach
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Indexing mobile objects using dual transformations
The VLDB Journal — The International Journal on Very Large Data Bases
A generic framework for monitoring continuous spatial queries over moving objects
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Efficient indexing of the historical, present, and future positions of moving objects
Proceedings of the 6th international conference on Mobile data management
GPAC: generic and progressive processing of mobile queries over mobile data
Proceedings of the 6th international conference on Mobile data management
Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes
IEEE Transactions on Knowledge and Data Engineering
Indexing the past, present, and anticipated future positions of moving objects
ACM Transactions on Database Systems (TODS)
Challenges in spatiotemporal stream query optimization
MobiDE '06 Proceedings of the 5th ACM international workshop on Data engineering for wireless and mobile access
Incremental Processing of Continual Range Queries over Moving Objects
IEEE Transactions on Knowledge and Data Engineering
IMPACT: a twin-index framework for efficient moving object query processing
Data & Knowledge Engineering
Indexing Spatio-Temporal Trajectories with Efficient Polynomial Approximations
IEEE Transactions on Knowledge and Data Engineering
Indexing future trajectories of moving objects in a constrained network
Journal of Computer Science and Technology
Query and update efficient B+-tree based indexing of moving objects
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
The Bdual-Tree: indexing moving objects by space filling curves in the dual space
The VLDB Journal — The International Journal on Very Large Data Bases
ST2B-tree: a self-tunable spatio-temporal b+-tree index for moving objects
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Proceedings of the 6th international conference on Mobile systems, applications, and services
SOLE: scalable on-line execution of continuous queries on spatio-temporal data streams
The VLDB Journal — The International Journal on Very Large Data Bases
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The VLDB Journal — The International Journal on Very Large Data Bases
Efficient security policy enforcement for the mobile environment
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Continuous Spatiotemporal Trajectory Joins
GeoSensor Networks
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Proceedings of the VLDB Endowment
A new approach on indexing mobile objects on the plane
Data & Knowledge Engineering
Position transformation: a location privacy protection method for moving objects
SPRINGL '08 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS
Improved partition method for tracking moving objects in road networks
International Journal of Advanced Intelligence Paradigms
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Transactions on Data Privacy
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SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Adaptive indexing of moving objects with highly variable update frequencies
Journal of Computer Science and Technology
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Proceedings of the 5th Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services
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Geoinformatica
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Design and evaluation of trajectory join algorithms
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Optimizing moving queries over moving object data streams
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ACM Transactions on Database Systems (TODS)
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Information Systems
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The VLDB Journal — The International Journal on Very Large Data Bases
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Optimizing predictive queries on moving objects under road-network constraints
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
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Forecasting region search of moving objects
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TrajPattern: mining sequential patterns from imprecise trajectories of mobile objects
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
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Towards optimal utilization of main memory for moving object indexing
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PA-tree: a parametric indexing scheme for spatio-temporal trajectories
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WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
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Hi-index | 0.00 |
Moving object databases are required to support queries on a large number of continuously moving objects. A key requirement for indexing methods in this domain is to efficiently support both update and query operations. Previous work on indexing such databases can be broadly divided into categories: indexing the past positions and indexing the future predicted positions. In this paper we focus on an efficient indexing method for indexing the future positions of moving objects.In this paper we propose an indexing method, called STRIPES, which indexes predicted trajectories in a dual transformed space. Trajectories for objects in d-dimensional space become points in a higher-dimensional 2d-space. This dual transformed space is then indexed using a regular hierarchical grid decomposition indexing structure. STRIPES can evaluate a range of queries including time-slice, window, and moving queries. We have carried out extensive experimental evaluation comparing the performance of STRIPES with the best known existing predicted trajectory index (the TPR*-tree), and show that our approach is significantly faster than TPR*-tree for both updates and search queries.