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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Munir, A. Gordon-Ross, A. Lysecky, S. Lysecky, R. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, University of Arizona, Tucson, USA (Lysecky, S.; Lysecky, R.) || Department of Electrical and Computer Engineering, University of Florida, Gainesville, USA (Munir, A.; Gordon-Ross, A.) |
| Abstract | Technological advancements in wireless communications and embedded systems have led to the proliferation of wireless sensor network (WSN) applications, each with varying application requirements (i.e., lifetime, throughput, reliability, etc.). Sensor node tunable parameters enable WSN designers to specialize/tune a sensor node to meet application requirements, but however, parameter tuning is a challenging process that requires designer expertise to consider sensor node complexities and changing environmental stimuli. In this paper, we develop lightweight, online optimization algorithms for sensor node parameter tuning, which enables dynamic optimizations to meet application requirements and adapt to changing environmental stimuli. Results reveal that our online optimizations quickly converge to a near optimal solution using minimal computational and storage resources, and are thus amenable for implementation on resource and energy-constrained sensor nodes. |
| Starting Page | 180 |
| Ending Page | 187 |
| File Size | 600513 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457720703 |
| e-ISBN | 9781457720710 |
| DOI | 10.1109/CCNC.2012.6181082 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-01-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Optimization Heuristic algorithms Wireless sensor networks Algorithm design and analysis Tuning Throughput Measurement low-power dynamic optimization lightweight |
| Content Type | Text |
| Resource Type | Article |
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