Title:
Mondrian Tree: Efficient Indexing Structure for Scalable Spatial Triggers Processing over Mobile Environment
Mondrian Tree: Efficient Indexing Structure for Scalable Spatial Triggers Processing over Mobile Environment
Author(s)
Doo, Myungcheol
Liu, Ling
Narasimhan, Nitya
Vasudevan, Venu
Liu, Ling
Narasimhan, Nitya
Vasudevan, Venu
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Abstract
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.
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Date Issued
2010
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Text
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Technical Report