Efficient indexing structure for scalable processing of spatial alarms

Authors:
Myungcheol Doo;Ling Liu;Nitya Narasimhan;Venu Vasudevan
Affiliations:
Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA;Applied Research Center, Motorola, Schaumburg, IL;Applied Research Center, Motorola, Schaumburg, IL
Venue:
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Year:
2010

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Abstract

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 savings of both server load and client-to-server communication cost. We evaluate the efficiency of the Mondrian tree indexing approach and show that the Mondrian tree offers significant performance enhancements on spatial alarm processing at both the server side and the client side.