Elements of information theory
Elements of information theory
Ten lectures on wavelets
Feedback Control of Dynamic Systems
Feedback Control of Dynamic Systems
Distributed optimization in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Evaluating local contributions to global performance in wireless sensor and actuator networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Distributed EM algorithms for density estimation and clustering in sensor networks
IEEE Transactions on Signal Processing
Collaborative beamforming for distributed wireless ad hoc sensor networks
IEEE Transactions on Signal Processing
Power scheduling of universal decentralized estimation in sensor networks
IEEE Transactions on Signal Processing
Energy-constrained modulation optimization
IEEE Transactions on Wireless Communications
Estimating inhomogeneous fields using wireless sensor networks
IEEE Journal on Selected Areas in Communications
Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks
IEEE Journal on Selected Areas in Communications
Connectivity and coverage maintenance in wireless sensor networks
The Journal of Supercomputing
Pattern based routing for event driven wireless sensor-actor networks
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
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We previously presented a model for some wireless sensor and actuator network (WSAN) applications based on the vector space tools of frame theory. In this WSAN model there is a weight associated to each sensor-actuator link denoting the importance of that communication link to the actuation fidelity. These weights were shown to be useful in pruning away communication links to reduce the number of active channels. Inspired by recent work in power scheduling for decentralized estimation, we investigate the optimal allocation of system resources for achieving a desired actuation fidelity. In this scheme, each sensor acquires a noisy observation and sends a message to a subset of actuators using an MQAM transmission strategy. The message sent on each sensor-actuator communication link is quantized with a variable number of bits, with the number of bits optimized to minimize the total network power consumption subject to a constraint on the actuation distortion. We show analytically and verify through simulation that performing this optimal power scheduling can yield significant power savings over communication strategies that use a fixed number of bits on each communication link.