Mesh Simplification for Centralized Algorithms

This is the first of a two-part investigation of centralized and decentralized approaches for determining the optimal configuration of a sensor network. In this first part, we present a centralized approach for the generation of mesh (wireless sensor) network configurations that provide complete sensing coverage and communication connectivity of a domain. A challenging problem in deploying wireless sensor networks is maximizing coverage in irregular shaped polygonal areas while maintaining a high degree of node connectivity. The novelties presented in this paper are: 1) a centralized mesh simplification technique, the Iterative Node Removal with Constrained Delaunay Triangulation and Smoothing (INRCDTS) algorithm, and 2) a centralized mesh generation approach with INRCDTS that may be used for any nonintersecting closed polygonal area.

Additionally, we provide a comparison of two centralized mesh generation techniques. The INRCDTS was built and tested as an enhancement of two traditional mesh generation techniques: advancing front technique and Matlab partial differential equation toolbox. The INCRCDTS introduces the ability to tune the generated mesh configuration to the number of nodes and nodal spacing. The INRCDTS enhancement has proven to increase the uniformity of the mesh in an irregular shaped polygonal area relative to advancing front and MATLABpartial differential equation algorithms by 23% and 41%, respectively.