A master thesis from Aalborg University
Modelling Dynamic Networks in OMNeT++ with a Traffic Engineering Genetic Algorithm
Author(s)
Term
4. term
Education
Publication year
2023
Submitted on
2023-06-16
Pages
28 pages
Abstract
We explore the domain of realistic simulation of dynamically changing networks. Throughout this exploration we define and implement a complete packet-level simulation framework and quickly manage changes in a dynamic network. This is accomplished by our utilization of the discrete event simulator OMNeT++ and our own non-trivial extensions of the simulation tool. Furthermore we also analyze and transform real world traffic data from a large European ISP, leveraging the realism of the traffic data to improve the otherwise static traffic demands of the Internet Topology Zoo. Finally we contribute with our own genetic algorithm Spungeet, as a means of swiftly reacting to the constant changes of a parallel running network. Spungeet leverages the fact that the order in which demands are routed makes a large difference in the ability to deliver the packets and thus it is evident that mapping the demands to individuals will enable quick generation of well performing data planes for the network. The Spungeet algorithm tries to maximize the percentage of packet delivery and performs well in both scenarios with and without failures.
Keywords
Documents
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