Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Introduction to Algorithms
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A generic framework for monitoring continuous spatial queries over moving objects
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
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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ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries
IEEE Transactions on Mobile Computing
When location-based services meet databases
Mobile Information Systems
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Scalable network distance browsing in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ICWE '08 Proceedings of the 2008 Eighth International Conference on Web Engineering
Spatio-temporal network databases and routing algorithms: a summary of results
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Preference query evaluation over expensive attributes
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Efficient k-nearest neighbor search in time-dependent spatial networks
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
The islands approach to nearest neighbor querying in spatial networks
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Towards k-nearest neighbor search in time-dependent spatial network databases
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks
Distributed and Parallel Databases
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K-nearest-neighbor (k-NN) queries have been widely studied in time-independent and time-dependent spatial networks. In this paper, we focus on k-NN queries in time-dependent spatial networks where the driving time between two locations may vary significantly at different time of the day. In practice, it is costly for a database server to collect real-time traffic data from vehicles or roadside sensors to compute the best route from a user to an object of interest in terms of the driving time. Thus, we design a new spatial query processing paradigm that uses a spatial mashup to enable the database server to efficiently evaluate k-NN queries based on the route information accessed from an external Web mapping service, e.g., Google Maps, Yahoo! Maps and Microsoft Bing Maps. Due to the expensive cost and limitations of retrieving such external information, we propose a new spatial query processing algorithm that uses shared execution through grouping objects and users based on the road network topology and pruning techniques to reduce the number of external requests to the Web mapping service and provides highly accurate query answers. We implement our algorithm using Google Maps and compare it with the basic algorithm. The results show that our algorithm effectively reduces the number of external requests by 90% on average with high accuracy, i.e., the accuracy of estimated driving time and query answers is over 92% and 87%, respectively.