Closest pair queries in spatial databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Filtering algorithms and implementation for very fast publish/subscribe systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
IEEE Transactions on Computers
Kinetic data structures
Roads, codes, and spatiotemporal queries
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Efficient constraint processing for location-aware computing
Proceedings of the 6th international conference on Mobile data management
Demo: a framework for location information processing
Proceedings of the 6th international conference on Mobile data management
iDistance: An adaptive B+-tree based indexing method for nearest neighbor search
ACM Transactions on Database Systems (TODS)
An efficient and scalable approach to CNN queries in a road network
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Efficient Processing of Continual Range Queries for Location-Aware Mobile Services
Information Systems Frontiers
Continuous nearest neighbor monitoring in road networks
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Distance indexing on road networks
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Adaptive location constraint processing
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Query processing in spatial network databases
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
Efficient constraint processing for highly personalized location based services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Scalable network distance browsing in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Expressive Location-Based Continuous Query Evaluation with Binary Decision Diagrams
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient location constraint processing for location-aware computing
Efficient location constraint processing for location-aware computing
Towards highly parallel event processing through reconfigurable hardware
Proceedings of the Seventh International Workshop on Data Management on New Hardware
Efficient batch processing of proximity queries by optimized probing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Efficient proximity detection among mobile objects in road networks with self-adjustment methods
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Applications ranging from location-based services to multi-player online gaming require continuous query support to monitor, track, and detect events of interest among sets of moving objects. Examples are alerting capabilities for detecting whether the distance, the travel cost, or the travel time among a set of moving objects exceeds a threshold. These types of queries are driven by continuous streams of location updates, simultaneously evaluated over many queries. In this paper, we define three types of proximity relations that induce location constraints to model continuous spatio-temporal queries among sets of moving objects in road networks. Our focus lies on evaluating a large number of continuous queries simultaneously. We introduce a novel moving object indexing technique that together with a novel road network partitioning scheme restricts computations within the partial road network. These techniques reduce query processing overhead by more than 95%. Experiments over real-world data sets show that our approach is twenty times faster than a baseline algorithm.