The Community for Technology Leaders
2013 IEEE 29th International Conference on Data Engineering (ICDE) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 1125-1128
Kai-Uwe Sattler , Department of Computer Science&Automation, Ilmenau University of Technology, Germany
Katja Hose , Department of Computer Science&Automation, Ilmenau University of Technology, Germany
Daniel Klan , Department of Computer Science&Automation, Ilmenau University of Technology, Germany
Marcel Karnstedt , Digital Enterprise Research Institute, National University of Ireland, Galway
ABSTRACT
Sensor networks have evolved to a powerful infrastructure component for event monitoring in many application scenarios. In addition to simple filter and aggregation operations, an important task in processing sensor data is data mining - the identification of relevant information and patterns. Limited capabilities of sensor nodes in terms of storage and processing capacity, battery lifetime, and communication demand a power-efficient, preferably sensor-local processing. In this paper, we present AnduIN, a system for developing, deploying, and running in-network data mining tasks. The system consists of a data stream processing engine, a library of operators for sensor-local processing, a box-and-arrow editor for specifying data mining tasks and deployment, a GUI providing the user with current information about the network and running queries, and an alerter notifying the user if a better query execution plan is available. At the demonstration site, we plan to show our system in action using burst detection as example application.
INDEX TERMS
CITATION
Kai-Uwe Sattler, Katja Hose, Daniel Klan, Marcel Karnstedt, "Power-aware data analysis in sensor networks", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 1125-1128, 2010, doi:10.1109/ICDE.2010.5447760
93 ms
(Ver 3.1 (10032016))