Multivariate interpolation of large sets of scattered data
ACM Transactions on Mathematical Software (TOMS)
Issues in data stream management
ACM SIGMOD Record
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
A quadtree approach to domain decomposition for spatial interpolation in grid computing environments
Parallel Computing - Special issue: High performance computing with geographical data
Nile-PDT: a phenomenon detection and tracking framework for data stream management systems
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Detection and tracking of discrete phenomena in sensor-network databases
SSDBM'2005 Proceedings of the 17th international conference on Scientific and statistical database management
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
SOLE: scalable on-line execution of continuous queries on spatio-temporal data streams
The VLDB Journal — The International Journal on Very Large Data Bases
The Rise of People-Centric Sensing
IEEE Internet Computing
Towards a streaming SQL standard
Proceedings of the VLDB Endowment
Towards window stream queries over continuous phenomena
Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoStreaming
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Technology advances have created a wide variety of novel, inexpensive sensors in the millimeter range that can be attached to or embedded into smartphones. These sensors are now directly connected to the Internet enabling us to collect high frequency updates from potentially thousands of mobile sensors densely deployed over an urban area. Today, data stream management systems (DSMS) are powerful data processing tools for update rates of 100,000-500,0000 tuples/s. In this paper, we investigate extending DSMS for monitoring continuous environmental phenomena such as air borne toxins or air quality based on up to 250K individual mobile sensor updates per query window to be spatially interpolated into a smooth, grid-based representation in near real-time. We propose a stream query operator approach and investigate different strategies to achieve near real-time spatial interpolation, while investigating memory footprint, runtime efficiency and interpolation quality of the different strategies.