On the Optimal Number of Smart Dust Particles

Authors: Samee Ullah Khan, C. Ardil

Abstract:

Smart Dust particles, are small smart materials used for generating weather maps. We investigate question of the optimal number of Smart Dust particles necessary for generating precise, computationally feasible and cost effective 3–D weather maps. We also give an optimal matching algorithm for the generalized scenario, when there are N Smart Dust particles and M ground receivers.

Keywords: Remote sensing, smart dust, matching, optimization.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328866

References:

[1] J. M. Kahn, R. H. Katz, and K. S. J. Pister, "Next century challenges: Mobile networking for smart dust," in MOBICOM, 1999, pp. 271-278.
[2] L. Doherthy, "Algorithms for position and data recovery in wireless sensor networks," Master-s thesis, University of California at Berkeley, June 2000.
[3] E. Vidal, L. Longpr'e, V. Kreinovich, and H. Haitao, "Geombinatorics of smart dust," Geombinatorics, vol. 11, no. 2, pp. 54-58, 2001.
[4] C. H. Papadimitriou and K. Steiglitz, Combinatorical Optimization: Algorithms and Complexity. Prentice Hall, 1982.
[5] R. E. Tarjan, "Data structures and network algorithms," CBMS-NSF Regional Conference Series in Applied Mathematics, vol. 44, 1983.
[6] N. Christofides, Graph Theory- an Algorithmic Approach. Academic Press, 1975.
[7] R. K. Ahuja, T. L. Magnanti, and J. B. Orlin, Network Flows: Theory, Algorithms and Applications. Prentice Hall, 1993.
[8] J. Edmonds, "Paths, trees, and flowers," Canadian Journal of Mathematics, vol. 17, pp. 449-467, 1965.