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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xu Cheng Ji Xu Jian Pei Jiangchuan Liu |
| Copyright Year | 2009 |
| Description | Author affiliation: School of Computing Science, Simon Fraser University, British Columbia, Canada (Xu Cheng; Ji Xu; Jian Pei; Jiangchuan Liu) |
| Abstract | Wireless sensor networks promise an unprecedented opportunity to monitor physical environments via inexpensive wireless embedded devices. Given the sheer amount of sensed data, efficient classification of them becomes a critical task in many sensor network applications. The large scale and the stringent energy constraints of such networks however challenge the conventional classification techniques that demand enormous storage space and centralized computation. In this paper, we propose a novel hierarchical distributed classification approach, in which local classifiers are built by individual sensors and merged along the routing path. The classifiers are iteratively enhanced by combining strategically generated pseudo data and new local data, eventually converging to a global classifier for the whole network. We demonstrate that our approach maintains high classification accuracy with very low storage and communication overhead. It also addresses a critical issue of heterogeneous data distribution among the sensors. |
| Starting Page | 10 |
| Ending Page | 19 |
| File Size | 10897882 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781424451135 |
| DOI | 10.1109/MOBHOC.2009.5336999 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-10-12 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Temperature sensors Wireless sensor networks Base stations Animals Wildlife Training data Sensor phenomena and characterization Computer networks Distributed computing Monitoring |
| Content Type | Text |
| Resource Type | Article |
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