(Georgia Institute of Technology, 2011)
Doo, Myungcheol; Liu, Ling
One of the most challenging problems in scaling spatial alarm processing is to compute alarm free regions
(AFR) such that mobile objects traveling within an AFR can safely hibernate the alarm evaluation process
until approaching the nearest alarm of interest. In this paper we argue that maintaining an index of both
spatial alarms and empty regions (AFR in the context of spatial alarm processing) is critical for scalable
processing of spatial alarms. Unfortunately, conventional spatial indexing methods, such as R-tree family,
k-d tree, Quadtree, and Grid, are 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 outperforms traditional index methods, such
as R-tree, Grid, Quadtree, and k-d tree, for spatial alarm processing.
(Georgia Institute of Technology, 2010)
Doo, Myungcheol; Liu, Ling; Narasimhan, Nitya; Vasudevan, Venu
Spatial Alarms are reminders for mobile users upon their arrival
of certain spatial location of interest. Spatial alarm processing
requires meeting two demanding objectives: high
accuracy, which ensures zero or very low alarm misses, and
high scalability, which requires highly efficient and optimal
processing of spatial alarms. Existing techniques for processing
spatial alarms cannot solve these two problems at
the same time. In this paper we present the design and implementation
of a new indexing technique, Mondrian tree.
The Mondrian tree indexing method partitions the entire universe
of discourse into spatial alarm monitoring regions and
alarm-free regions. This enables us to reduce the number of
on-demand alarm-free region computations, significant saving
of both server load and client to server communication
cost. We evaluate the efficiency of the Mondrian tree indexing
approach using a road network simulator and show that
the Mondrian tree offers significant performance enhancements
on spatial alarm processing at both the server side and
the client side.