Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks
Network science provides essential tools to model and analyze topology and structure of dynamic wireless telemetry networks. In this paper, we model wireless telemetry networks using three well-known graph models: Gilbert random graph, Erdős-Rényi random graph, and random geometric graph models. Next, we analyze the connectivity of synthetically generated topologies using graph energy, which is the sum of absolute values of eigenvalues. Our results indicate second-order curves for adjacency and Laplacian energies as the connectivity of synthetically generated networks improve. The normalized Laplacian energy decreases, converging to the theoretical lower bound as the connectivity reaches to a maximum.
T. A. Shatto et al., "Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks," Proceedings of the 2017 International Telemetering Conference (2017, Las Vegas, NV), International Foundation for Telemetering, Oct 2017.
2017 International Telemetering Conference, ITC 2017 (2017: Oct. 23-26, Las Vegas, NV)
Electrical and Computer Engineering
Keywords and Phrases
Eigenvalues and eigenfunctions; Graph theory; Laplace transforms; Telemetering; Telemetering equipment; Absolute values; Energy analysis; Graph theoretic modeling; Network science; Normalized Laplacian; Random geometric graphs; Second orders; Wireless telemetry; Topology
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2017 The Author(s), All rights reserved.
01 Oct 2017