The LSD tree: spatial access to multidimensional and non-point objects
VLDB '89 Proceedings of the 15th international conference on Very large data bases
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
Multidimensional binary search trees used for associative searching
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
Computing the Largest Empty Rectangle
STACS '84 Proceedings of the Symposium of Theoretical Aspects of Computer Science
Techniques for Design and Implementation of Efficient Spatial Access Methods
VLDB '88 Proceedings of the 14th International Conference 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
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Efficient Construction of Safe Regions for Moving kNN Queries over Dynamic Datasets
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Scalable processing of spatial alarms
HiPC'08 Proceedings of the 15th international conference on High performance computing
RoadTrack: scaling location updates for mobile clients on road networks with query awareness
Proceedings of the VLDB Endowment
Place-Its: a study of location-based reminders on mobile phones
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
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With ubiquitous wireless connectivity and technological advances in mobile devices, we witness the growing demands and increasing market shares of mobile intelligent systems and technologies for real-time decision making and location-based knowledge discovery. Spatial alarms are considered as one of the fundamental capabilities for intelligent mobile location-based systems. Like time-based alarms that remind us the arrival of a future time point, spatial alarms remind us the arrival of a future spatial point. Existing approaches for scaling spatial alarm processing are focused on computing Alarm-Free Regions (Afr) and Alarm-Free Period (Afp) such that mobile objects traveling within an Afr can safely hibernate the alarm evaluation process for the computed Afp, to save battery power, until approaching the nearest alarm of interest. A key technical challenge in scaling spatial alarm processing is to efficiently compute Afr and Afp such that mobile objects traveling within an Afr can safely hibernate the alarm evaluation process during the computed Afp, while maintaining high accuracy. In this article we argue that on-demand computation of Afr is expensive and may not scale well for dense populations of mobile objects. Instead, we propose to maintain an index for both spatial alarms and empty regions (Afr) such that for a given mobile user's location, we can find relevant spatial alarms and whether it is in an alarm-free region more efficiently. We also show that conventional spatial indexing methods, such as R-tree family, k-d tree, Quadtree, and Grid, are by design not well suited to index empty regions. We present Mondrian Tree – a region partitioning tree for indexing both spatial alarms and alarm-free regions. We first introduce the Mondrian Tree indexing algorithms, including index construction, search, and maintenance. Then we describe a suite of Mondrian Tree optimizations to further enhance the performance of spatial alarm processing. Our experimental evaluation shows that the Mondrian Tree index, as an intelligent technology for mobile systems, outperforms traditional index methods, such as R-tree, Quadtree, and k-d tree, for spatial alarm processing.