Difference between revisions of "Megerian2005"
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|abstract=Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Here, we address one of the fundamental problems, namely, coverage. Sensor coverage, in general, answers the questions about the quality of service (surveillance) that can be provided by a particular sensor network. We briefly discuss the definition of the coverage problem from several points of view and formally define the worst and best-case coverage in a sensor network. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, we establish the main highlight of the paper - an optimal polynomial time worst and average case algorithm for coverage calculation for homogeneous isotropic sensors. We also present several experimental results and analyze potential applications, such as using best and worst-case coverage information as heuristics to deploy sensors to improve coverage. | |abstract=Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Here, we address one of the fundamental problems, namely, coverage. Sensor coverage, in general, answers the questions about the quality of service (surveillance) that can be provided by a particular sensor network. We briefly discuss the definition of the coverage problem from several points of view and formally define the worst and best-case coverage in a sensor network. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, we establish the main highlight of the paper - an optimal polynomial time worst and average case algorithm for coverage calculation for homogeneous isotropic sensors. We also present several experimental results and analyze potential applications, such as using best and worst-case coverage information as heuristics to deploy sensors to improve coverage. | ||
|pages=84 - 92 | |pages=84 - 92 | ||
|month= | |||
|year=2005 | |||
|volume=4 | |volume=4 | ||
|journal=IEEE Transactions on Mobile Computing | |journal=IEEE Transactions on Mobile Computing | ||
|title=Worst- and Best-Case Coverage in Sensor Networks | |title=Worst- and Best-Case Coverage in Sensor Networks | ||
|entry=article | |entry=article | ||
| | |pdf=Megerian2005.pdf | ||
}} | }} | ||
Latest revision as of 17:37, 9 November 2021
| Megerian2005 | |
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| author | S. Megerian and F. Koushanfar and M. Potkonjak and M. Srivastava |
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| journal | IEEE Transactions on Mobile Computing |
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| pages | 84 - 92 |
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| title | Worst- and Best-Case Coverage in Sensor Networks |
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| volume | 4 |
| year | 2005 |
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| Megerian2005.pdf | |
Email:
farinaz@ucsd.edu
farinaz@ucsd.edu
Address:
Electrical & Computer Engineering
University of California, San Diego
9500 Gilman Drive, MC 0407
Jacobs Hall, Room 6401
La Jolla, CA 92093-0407
Electrical & Computer Engineering
University of California, San Diego
9500 Gilman Drive, MC 0407
Jacobs Hall, Room 6401
La Jolla, CA 92093-0407
Lab Location: EBU1-2514
University of California San Diego
9500 Gilman Dr, La Jolla, CA 92093
University of California San Diego
9500 Gilman Dr, La Jolla, CA 92093