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By:Jennifer L. Wong
Published on 2006 by

The main goal of this thesis is to address three driver applications (manufacturing variability in integrated circuits, lossy links in wireless ad-hoc networks, and energy efficient sensing of a statistically predictable environment) using a systematic systems of NST-based modeling and optimization techniques. The consistent strategy is the use of collected data from traces of deployed or operational systems to drive both the analysis and realization of an embedded system. The analysis leverages on non-parametric statistical techniques and identifies design insights, tractable and accurate optimization objectives, and serves a basis for fast and realistic simulation. We address the use of statistical techniques at two different levels of embedded system design: during the IC design process, and during the application of embedded system components. At the IC design level, a statistical methodology is used for characterization of three variability issues mainly resultant from manufacturing variability: a priori wire-length estimation, wire-length estimation, and statistical timing analysis. At the distributed systems level, variability is addressed through modeling of lossy wireless link communication, in building a localized routing protocol, modeling of sensor phenomena, and for efficient node deployment.

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Book ID of Design of Embedded Systems Using Data-driven Statistical Techniques's Books is -WFZHwAACAAJ, Book which was written byJennifer L. Wonghave ETAG "1j3CA3BdvPA"

Book which was published by since 2006 have ISBNs, ISBN 13 Code is 9781109897289 and ISBN 10 Code is 1109897286

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