Realization using the Roesser model for implementations in distributed grid sensor networks
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Using the Roesser model, a method for distributed information processing in grid sensor networks is presented by Sumanasena and Bauer (A Roesser model based multidimensional systems approach for grid sensor networks. Pacific Grove, California, 2009). The method can be used to implement linear systems in grid sensor networks. Unless information originating in a node can be conveyed over the entire sensor network in a single time slot, for a system described by the Roesser model to be implementable in real-time on a sensor network, the system matrices of the Roesser model have to assume a particular form. A necessary and sufficient condition for a proper transfer matrix to be realizable in the constrained Roesser model is established in this paper. A realization algorithm to derive the Roesser model of the desired form, given an admissible transfer matrix is derived. The analogues problem for the realization of non-proper transfer matrices is also addressed.
KeywordsGrid sensor networks Roesser model Realization Distributed signal processing
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- Akbar, A., Mansoor, W., Chaudhry, S., Kashif, A., & Kim K. (2006). Node-link-failure resilient routing architecture for sensor grids. In The 8th international conference advanced communication technology (pp. 131–135). Phoenix, USA.Google Scholar
- Barrenechea. G., & Beferull-Lozano, B., Vetterli, M. (2004). Lattice sensor networks: capacity limits, optimal routing and robustness to failures. In Proceedings of the 3rd international symposium on information processing in sensor networks (pp. 186–195). Berkeley, USA.Google Scholar
- Bose N. (2003) Multidimensional systems theory and applications. Kluwer Academic PublishersGoogle Scholar
- Dewasurendra, D. A., & Bauer, P. H. (2008). A novel approach to grid sensor networks. In 15th IEEE International Conference on Electronics, Circuits and Systems, Malta, pp. 1191–1194Google Scholar
- Fan, H., Xu, L., & Lin, Z. (2006). A constructive procedure for three-dimensional realization. In Proceedings of the 6th world congress on intelligent control and automation (pp. 1893–1896). Dalian, China.Google Scholar
- Huang. Y., Loewke, K., Schaaf, K., & Nemat-Nasser, S. (2005). Localized SHM with embedded sensor network. In Proceedings of the 5th international workshop on structural health monitoring (pp. 1554–1561). Stanford.Google Scholar
- Leoncini M, Resta G, & Santi P (2005) Analysis of a wireless sensor dropping problem in wide-area environmental monitoring. In Proceedings of the 4th international symposium on information processing in sensor networks (pp. 239–245). Los Angeles, California.Google Scholar
- Shakkottai, S., Srikant, R., & Shroff, N. (2003). Unreliable sensor grids: Coverage, connectivity and diameter. In Proceedings of IEEE INFOCOM (pp. 1073–1083). San Francisco.Google Scholar
- Sumanasena, M. G. B., & Bauer, P. H. (2008). Distributed m-d filtering for wave front detection in grid sensor networks. In Proceedings of the 20th IASTED international conference on parallel and distributed computing and systems (pp. 423–429). Orlando, Florida.Google Scholar
- Sumanasena, M. G. B., Bauer, P. H. (2009). A Roesser model based multidimensional systems approach for grid sensor networks. In 43rd asilomar conference on signals systems and computers. California: Pacific Grove.Google Scholar
- Xu, K., Takahara, G., & Hassanein, H. (2006). On the robustness of grid-based deployment in wireless sensor networks. In Proceedings of the 2006 international conference on wireless communications and mobile computing (pp. 1183–1188). Canada: Vancouver.Google Scholar