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Proceedings Paper

Adaptive smart sensor webs with predictive control for workflow and resource management in dynamic environments
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Paper Abstract

A novel predictive controller framework is discussed for integrated smart sensing and resource management in a distributed intelligent sensor network with sensor nodes whose useful active lifetime is significantly shorter than the required lifetime of the sensor system. Past sensor network research has focused on security and communication, but largely ignored the overall dynamic resource management issue of such distributed systems. Our contribution is in integrated control optimization and resource management algorithms to ensure proper functioning of distributed sensors in extremely limited bandwidth, power, and storage. In this paper, we present a novel genetic algorithm (GA) for real-time system control and resource management that handles multiple conflicting objectives and constraints in the distributed system. We suggest using a GA-based predictive controller to give optimal actions that account for future states and future possible events while estimating the optimal control action policy. Our framework is suitable for dynamic environments where the desired system performance and resource usage changes dynamically while being constrained by limited amount of resources.

Paper Details

Date Published: 17 April 2006
PDF: 12 pages
Proc. SPIE 6245, Optical Pattern Recognition XVII, 624506 (17 April 2006); doi: 10.1117/12.665755
Show Author Affiliations
Ashit Talukder, CHLA, Univ. of Southern California (United States)
Jet Propulsion Lab. (United States)
S. Monacos, CHLA, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 6245:
Optical Pattern Recognition XVII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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