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WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
An Algorithm for Computing the Overlay of k-Dimensional Spaces
SSD '91 Proceedings of the Second International Symposium on Advances in Spatial Databases
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The VLDB Journal — The International Journal on Very Large Data Bases
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WISEW '02 Proceedings of the Third International Conference on Web Information Systems Engineering (Workshops) - (WISEw'02)
Main Memory Evaluation of Monitoring Queries Over Moving Objects
Distributed and Parallel Databases
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STRIPES: an efficient index for predicted trajectories
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Indexing mobile objects using dual transformations
The VLDB Journal — The International Journal on Very Large Data Bases
AGILE: adaptive indexing for context-aware information filters
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Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
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Indexing the past, present, and anticipated future positions of moving objects
ACM Transactions on Database Systems (TODS)
Continuous nearest neighbor monitoring in road networks
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Scaling games to epic proportions
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Shakra: tracking and sharing daily activity levels with unaugmented mobile phones
Mobile Networks and Applications
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VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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
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VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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
Main-memory operation buffering for efficient R-tree update
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TRAX: real-world tracking of moving objects
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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
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The VLDB Journal — The International Journal on Very Large Data Bases
Towards optimal utilization of main memory for moving object indexing
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SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
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DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
MOVIES: indexing moving objects by shooting index images
Geoinformatica
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SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
DaMoN '12 Proceedings of the Eighth International Workshop on Data Management on New Hardware
Boosting moving object indexing through velocity partitioning
Proceedings of the VLDB Endowment
Continuous queries on trajectories of moving objects
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Predictive line queries for traffic prediction
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
Predictive spatio-temporal queries: a comprehensive survey and future directions
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Indexing methods for moving object databases: games and other applications
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RUM+-tree: a new multidimensional index supporting frequent updates
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
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A pure peer-to-peer approach for kNN query processing in mobile ad hoc networks
Personal and Ubiquitous Computing
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With the exponential growth of moving objects data to the Gigabyte range, it has become critical to develop effective techniques for indexing, updating, and querying these massive data sets. To meet the high update rate as well as low query response time requirements of moving object applications, this paper takes a novel approach in moving object indexing. In our approach we do not require a sophisticated index structure that needs to be adjusted for each incoming update. Rather we construct conceptually simple short-lived throwaway indexes which we only keep for a very short period of time (sub-seconds) in main memory. As a consequence, the resulting technique MOVIES supports at the same time high query rates and high update rates and trades this for query result staleness. Moreover, MOVIES is the first main memory method supporting time-parameterized predictive queries. To support this feature we present two algorithms: non-predictive MOVIES and predictive MOVIES. We obtain the surprising result that a predictive indexing approach -- considered state-of-the-art in an external-memory scenario -- does not scale well in a main memory environment. In fact our results show that MOVIES outperforms state-of-the-art moving object indexes like a main-memory adapted B x -tree by orders of magnitude w.r.t. update rates and query rates. Finally, our experimental evaluation uses a workload unmatched by any previous work. We index the complete road network of Germany consisting of 40,000,000 road segments and 38,000,000 nodes. We scale our workload up to 100,000,000 moving objects, 58,000,000 updates per second and 10,000 queries per second which is unmatched by any previous work.