POCO-MOEA: Using Evolutionary Algorithms to Solve the Controller Placement Problem

Abstract

One of the central tenets of a Software Defined Network (SDN) is the use of controllers, which are responsible for managing how traffic flows through switches, routers, and other data passing devices on a computer network. Most modern SDNs use multiple controllers to divide responsibility for network switches while keeping communication latency low. A problem that has emerged since approximately 2011 is the decision of where to place these controllers to create the most 'optimum' network. This is known as the Controller Placement Problem (CPP). Such a decision is subject to multiple and sometimes conflicting goals, making the CPP a type of Multi-Objective Problem (MOP). The theory of this thesis is that an MOEA can produce solutions to the CPP which are 'nearly optimal' while keeping execution time low compared to an exhaustive 'optimal' search. This research extends a network modeling tool called the Pareto Optimal Controller Placement (POCO) Framework with custom designed MOEA, called POCO-MOEA.

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Document Details

Document Type
Technical Report
Publication Date
Mar 24, 2016
Accession Number
AD1053821

Entities

People

  • Scott I. Harned

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Application Software
  • Computational Complexity
  • Computer Networks
  • Computer Programming
  • Computers
  • Department Of Defense
  • Evolutionary Algorithms
  • Governments
  • Graphical User Interface
  • Network Protocols
  • Network Topology
  • Performance Tests
  • Software Defined Networks
  • Two Dimensional
  • United States Government

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Networking
  • Operations Research