We explore the domain of realistic simulation of dynamicallychanging networks. Throughout this exploration we define and implement a complete packet-level simulation framework and quickly managechanges in a dynamic network. This is accomplished by our utilization ofthe discrete event simulator OMNeT++ and our own non-trivial extensions of the simulation tool. Furthermore we also analyze and transformreal world traffic data from a large European ISP, leveraging the realism of the traffic data to improve the otherwise static traffic demandsof the Internet Topology Zoo. Finally we contribute with our own genetic algorithm Spungeet, as a means of swiftly reacting to the constantchanges of a parallel running network. Spungeet leverages the fact thatthe order in which demands are routed makes a large difference in theability to deliver the packets and thus it is evident that mapping thedemands to individuals will enable quick generation of well performingdata planes for the network. The Spungeet algorithm tries to maximizethe percentage of packet delivery and performs well in both scenarioswith and without failures.