Abstract
Wireless sensor networks are often studied with the goal of removing information from the network as efficiently as possible. However, when the application also includes an actuator network, it is advantageous to determine actions in-network. In such settings, optimizing the sensor node behavior with respect to sensor information fidelity does not necessarily translate into optimum behavior in terms of action fidelity. Inspired by neural systems, we present a model of a sensor and actuator network based on the vector space tools of frame theory that applies to applications analogous to reflex behaviors in biological systems. Our analysis yields bounds on both absolute and average actuation error that point directly to strategies for limiting sensor communication based not only on local measurements but also on a measure of how important each sensor-actuator link is to the fidelity of the total actuation output.
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References
Nowak, R.D.: Distributed EM algorithms for density estimation and clustering in sensor networks. IEEE Transactions on Signal Proc. 51, 2245–2253 (2003)
Rabbat, M., Nowak, R.D.: Distributed optimization in sensor networks. In: Intl. Symposium on Information Proc. in Sensor Networks (IPSN), Berkeley, CA (2004)
Blatt, D., Hero, A.O.: Distributed maximum likelihood estimation in sensor networks. In: Intl. Conf. on Acoustics, Speech, and Signal Proc., Montreal, Canada (2004)
Liu, J., Chu, M., Liu, J., Reich, J.E., Zhao, F.: State-centric programming for sensor and actuator network systems. IEEE Pervasive Computing Magazine 2(4) (2003)
Gerkey, B., Mataric, M.: A market-based formulation of sensor-actuator network coordination. In: AAAI Spring Symp. on Intel. Embed. and Dist. Sys., AAAI Press, Menlo Park (2002)
Coates, M.: Evaluating causal relationships in wireless sensor/actuator networks. In: Intl. Conf. on Acoustics, Speech, and Signal Proc., Philadelphia, PA (2005)
Lemmon, M.D., Ling, Q., Sun, Y.: Overload management in sensor-actuator networks used for spatially-distributed control systems. In: Proceedings of the ACM Sensys Conference (2003)
Kandel, E., Schwartz, J., Jessell, T.: Principles of Neural Science. Appleton & Lange, Norwalk, CT (1991)
Neil, D.M.: Compensatory eye movements. In: Sandeman, D., Atwood, H. (eds.) The Biology of Crustacea, Neural Integration and Behavior, pp. 133–163. Academic Press, New York (1982)
Glantz, R., Nudelman, H., Waldrop, B.: Linear integration of convergent visual inputs in an oculomotor reflex pathway. J. of Neurophys. 52(6), 1213–1225 (1984)
Nowak, R., Mitra, U., Willett, R.: Estimating inhomogeneous fields using wireless sensor networks. IEEE J. on Selected Areas in Comm. 22(6), 999–1006 (2004)
Christensen, O.: An Introduction to Frames and Riesz Bases. Birkhauser, Boston, MA (2002)
Duffin, R., Schaeffer, A.: A class of nonharmonic Fourier series. Transactions of the American Mathematical Society 72(2), 341–366 (1952)
Daubechies, I.: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, Philadelphia, PA (1992)
Bolcskei, H., Hlawatsch, F., Feichtinger, H.: Frame-theoretic analysis of oversampled filter banks. IEEE Transactions on Signal Proc. 46(12), 3256–3268 (1998)
Candès, E., Donoho, D.: New tight frames of curvelets and optimal representations of objects with piecewise C 2 singularities. Communications on Pure and Applied Mathematics 57(2), 219–266 (2004)
Strohmer, T., Heath Jr., R.: Grassmannian frames with applications to coding and communcations. Applied and Comp. Harmonic Analysis 14(3), 257–275 (2003)
Goyal, V., Kovačević, J., Kelner, J.: Quantized frame expansions with erasures. Applied and Computational Harmonic Analysis 10, 203–233 (2001)
Gao, J., Harris, C., Gunn, S.: On a class of support vector kernels based on frames in function hilbert spaces. Neural Computation 13, 1975–1994 (2001)
Balan, R., Casazza, P., Heil, C., Landau, Z.: Density, overcompleteness, and localization of frames, I. Theory (preprint, 2005)
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Rozell, C.J., Johnson, D.H. (2006). Evaluating Local Contributions to Global Performance in Wireless Sensor and Actuator Networks. In: Gibbons, P.B., Abdelzaher, T., Aspnes, J., Rao, R. (eds) Distributed Computing in Sensor Systems. DCOSS 2006. Lecture Notes in Computer Science, vol 4026. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11776178_1
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DOI: https://doi.org/10.1007/11776178_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35227-3
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