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Cross-Layer Network Design using Controllers

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Date Issued:
2007
Summary:
A cross-layer design architecture featuring a new network stack component called a controller is presented. The controller takes system status information from the protocol components and uses it to tune the behavior of the network stack to a given performance objective. A controller design strategy using a machine learning algorithm and a simulator is proposed, implemented, and tested. Results show the architecture and design strategy are capable of producing a network stack that outperforms the existing protocol stack for arbitrary performance objectives. The techniques presented give network designers the flexibility to easily tune the performance of their networks to suit their application. This cognitive networking architecture has great potential for high performance in future wireless networks.
Title: Cross-Layer Network Design using Controllers.
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Name(s): Slavik, Michael J.
Mahgoub, Imad, Thesis advisor
Florida Atlantic University, Degree grantor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2007
Date Issued: 2007
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 124 p.
Language(s): English
Summary: A cross-layer design architecture featuring a new network stack component called a controller is presented. The controller takes system status information from the protocol components and uses it to tune the behavior of the network stack to a given performance objective. A controller design strategy using a machine learning algorithm and a simulator is proposed, implemented, and tested. Results show the architecture and design strategy are capable of producing a network stack that outperforms the existing protocol stack for arbitrary performance objectives. The techniques presented give network designers the flexibility to easily tune the performance of their networks to suit their application. This cognitive networking architecture has great potential for high performance in future wireless networks.
Identifier: FA00012555 (IID)
Degree granted: Thesis (M.S.)--Florida Atlantic University, 2007.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Subject(s): Computer architecture
Wireless communication systems--Design and construction
Evolutionary programming (Computer science)
Mathematical optimization
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00012555
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.