Spectral Graph Theory Analysis of Software-Defined Networks to Improve Performance and Security

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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2015
Accession Number
ADA632374

Entities

People

  • Thomas C. Parker

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Change Detection
  • Closed Loop Systems
  • Command And Control
  • Computational Science
  • Computer Networks
  • Control Systems
  • Control Systems Engineering
  • Digital Communications
  • Feature Extraction
  • Graph Theory
  • Kalman Filters
  • Mesh Networks
  • Network Protocols
  • Network Science
  • Network Topology
  • Software Defined Networks

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Cybersecurity.
  • Robotics and Automation.