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dc.contributor.advisorCetinkaya, Egemen K.en
dc.contributor.advisorKosbar, Kurten
dc.contributor.authorShatto, Tristan A.
dc.date.accessioned2018-03-02T22:55:34Z
dc.date.available2018-03-02T22:55:34Z
dc.date.issued2017-10
dc.identifier.issn0884-5123
dc.identifier.issn0074-9079
dc.identifier.urihttp://hdl.handle.net/10150/626977
dc.description.abstractNetwork 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.
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.language.isoen_USen
dc.publisherInternational Foundation for Telemeteringen
dc.relation.urlhttp://www.telemetry.org/en
dc.rightsCopyright © held by the author; distribution rights International Foundation for Telemeteringen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.titleGraph Theoretic Modeling and Energy Analysis of Wireless Telemetry Networksen_US
dc.typetexten
dc.typeProceedingsen
dc.contributor.departmentTelemetry Learning Center Department of Electrical and Computer Engineering, Missouri University of Science and Technologyen
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
refterms.dateFOA2018-05-17T23:29:29Z
html.description.abstractNetwork 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.


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