Accession Number:

AD1053259

Title:

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

Descriptive Note:

Technical Report,01 May 2014,24 Mar 2016

Corporate Author:

AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States

Personal Author(s):

Report Date:

2016-03-24

Pagination or Media Count:

132.0

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.

Subject Categories:

  • Computer Programming and Software
  • Computer Systems Management and Standards

Distribution Statement:

APPROVED FOR PUBLIC RELEASE