Abstract

This paper is devoted to sensor scheduling for a class of sensor networks whose sensors are spatially distributed and measurements are influenced by state dependent noise. Sensor scheduling is required to achieve power saving since each sensor operates with a battery power source. The sensor scheduling problem is formulated as model predictive control which minimizes a quadratic cost function with communication costs, since communications among sensors take much power. A fast and optimal sensor scheduling algorithm is proposed for a class of sensor networks. From a theoretical standpoint, we present that computation time of the proposed algorithm increases exponentially with the number of sensor types, while that of standard algorithms is exponential in the number of the sensors. The proposed algorithm is faster than standard one, since the number of sensor types is always less than or equal to the number of sensors.

Full Text

Published Version

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.