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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gning, A. Mihaylova, L. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Communication Systems, InfoLab21 Lancaster University, LA1 4WA, UK (Gning, A.; Mihaylova, L.) |
| Abstract | A fundamental issue in real-world monitoring network systems is the choice of sensors to track local events. Ideally, the sensors work together, in a distributed manner, to achieve a common mission-specific task. This paper develops a framework for distributed inference based on dynamic clustering and belief propagation in sensor networks with deficient links. We investigate this approach for dynamic clustering of sensor nodes combined with belief propagation for the purposes of object tracking in sensor networks with and without deficient links. We demonstrate the efficiency of our approach over an example of hundreds randomly deployed sensors. |
| Starting Page | 656 |
| Ending Page | 663 |
| File Size | 2330942 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780982443804 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | ISIF |
| Subject Keyword | Belief propagation Sensor systems Condition monitoring Wireless sensor networks Sensor fusion Markov random fields Collaborative work Energy efficiency Dynamic scheduling Aircraft distributed inference dynamic clustering sensor networks object tracking communication failures |
| Content Type | Text |
| Resource Type | Article |
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