Wireless Sensor Networks: An Information Processing Approach
Wireless Sensor Networks: An Information Processing Approach
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Preserving local topological relationships
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Decentralized querying of topological relations between regions without using localization
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Detecting change in snapshot sequences
GIScience'10 Proceedings of the 6th international conference on Geographic information science
Efficient tracking of 2D objects with spatiotemporal properties in wireless sensor networks
Distributed and Parallel Databases
Tracking continuous topological changes of complex moving regions
Proceedings of the 2011 ACM Symposium on Applied Computing
Efficient, Decentralized Computation of the Topology of Spatial Regions
IEEE Transactions on Computers
COSIT'11 Proceedings of the 10th international conference on Spatial information theory
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With the development of miniaturized sensor and communication technologies, there is an ever-growing demand for algorithms to derive high-level spatiotemporal events from large amounts of sensed data. Our previous work has already defined a decentralized, in-network approach to identifying topological relation changes between continuously evolving regions monitored by a geosensor network. However, our previous work relies on a number of strong continuity assumptions, concerning the temporal granularity of sensor observations and the type of region deformations. This paper presents an improved algorithm which demonstrates how these key simplifying assumptions can be relaxed. Empirical testing of the algorithm demonstrates how this algorithm can operate at higher levels of scalability than both the previous algorithm, and smart centralized alternatives.