Andrew Thaeler

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3 Centralized CDS Construction 335 3.1 Guha and Khuller’s Algorithm . . . . . . . . . . . . . . . . . . . . . 336 3.2 Ruan’s Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 3.3 Cheng’s Greedy Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 340 3.4 Min’s Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341(More)
We present a novel time-based positioning scheme (TPS) for efficient location discovery in outdoor sensor networks. TPS relies on TDoA (time-difference-of-arrival) of RF signals measured locally at a sensor to detect range differences from the sensor to three base stations. These range differences are averaged over multiple beacon intervals before they are(More)
We introduce and study the localization problem in large scale underwater acoustic sensor networks. Considering that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two-dimensional counterpart via a projection technique. We then introduce a localization scheme specifically designed(More)
Fault-tolerant target detection and localization is a challenging task in collaborative sensor networks. This paper introduces our exploratory work toward identifying the targets in sensor networks with faulty sensors. We explore both spatial and temporal dimensions for data aggregation to decrease the false alarm rate and improve the target position(More)
In this paper, we present time-based positioning scheme (iTPS), a purely localized location detection scheme for sensor networks with long-range beacons. iTPS relies on time difference of arrival (TDoA) of radio frequency (RF) signals measured locally at each sensor to detect range differences from the sensor to four base stations. These range differences(More)
Fault-tolerant target detection and localization is a challenging task in collaborative sensor networks. The paper introduces our exploratory work toward identifying a stationary target in sensor networks with faulty sensors. We explore both spatial and temporal dimensions for data aggregation to decrease the false alarm rate and improve the target position(More)
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