Spectral graph theory analysis of software-defined networks to improve performance and security

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Authors
Parker, Thomas C.
Subjects
Software-defined network
networking
cybersecurity
eigenvalue
eigenvector
graph theory
spectral graph theory
control theory
Advisors
Tummala, Murali
McEachen, John
Date of Issue
2015-09
Date
Sep-15
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Software-defined networks are revolutionizing networking by providing unprecedented visibility into and control over data communication networks. The focus of this work is to develop a method to extract network features, develop a closed-loop control framework for a software-defined network, and build a test bed to validate the proposed scheme. The method developed to extract the network features is called the dual-basis analysis, which is based on the eigendecomposition of a weighted graph that accounts for the network topology and traffic load. A software-defined network closed-loop control scheme is developed; the scheme is modeled after a closed-loop control system that includes an observer and a controller. A particle filter and phantom node are used to estimate link data rates and identify the onset of congestion. Based on the outputs of the observer, the controller is able to balance traffic throughout the network to minimize congestion. A software-defined network test bed is developed to evaluate the proposed dual-basis representation and the closed-loop control scheme. The test bed is a real-world implementation of a software-defined network that consists of 13 switches and one controller. The test bed ensures that the proposed schemes are suitable even when applied in a hardware or software implementation.
Type
Thesis
Description
Series/Report No
Department
Computer and Electrical Engineering
Computer and Electrical Engineering
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Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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