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, Erdos-Renyi random graph, and random geometric graph models. Nex...
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ndltd-arizona.edu-oai-arizona.openrepository.com-10150-6269772018-03-09T03:00:41Z Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks Shatto, Tristan A. Cetinkaya, Egemen K. Kosbar, Kurt Telemetry Learning Center Department of Electrical and Computer Engineering, Missouri University of Science and Technology 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, Erdos-Renyi 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. 2017-10 text Proceedings 0884-5123 0074-9079 http://hdl.handle.net/10150/626977 http://arizona.openrepository.com/arizona/handle/10150/626977 International Telemetering Conference Proceedings en_US http://www.telemetry.org/ Copyright © held by the author; distribution rights International Foundation for Telemetering International Foundation for Telemetering |
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description |
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, Erdos-Renyi 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. |
author2 |
Cetinkaya, Egemen K. |
author_facet |
Cetinkaya, Egemen K. Shatto, Tristan A. |
author |
Shatto, Tristan A. |
spellingShingle |
Shatto, Tristan A. Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
author_sort |
Shatto, Tristan A. |
title |
Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
title_short |
Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
title_full |
Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
title_fullStr |
Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
title_full_unstemmed |
Graph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networks |
title_sort |
graph theoretic modeling and energy analysis of wireless telemetry networks |
publisher |
International Foundation for Telemetering |
publishDate |
2017 |
url |
http://hdl.handle.net/10150/626977 http://arizona.openrepository.com/arizona/handle/10150/626977 |
work_keys_str_mv |
AT shattotristana graphtheoreticmodelingandenergyanalysisofwirelesstelemetrynetworks |
_version_ |
1718616152486182912 |