Incremental deployment for traffic engineering in hybrid SDN network

Traffic engineering is a method to balance the flows and optimize the routing in the network. Software defined networking is a new network architecture and we can gain great benefit by migrating the traditional IP network to the SDN-enabled network from the perspective of traffic engineering. However, due to the economical, organizational and technical challenges, migrating to the network with a full deployment of SDN routers is impractical in the short term. It is a desirable choice to deploy SDN incrementally. In this paper, we seek to search for an optimal migration sequence of the legacy routers to SDN-enabled routers so that we can decide where and how many routers to migrate firstly. Our main contribution is that we propose a heuristic algorithm, i.e., genetic algorithm, to seek a migration sequence of the routers that obtains the most of the benefit from the perspective of traffic engineering. We evaluate the algorithm by conducting simulation experiments, making comparison to the greedy migration algorithm and static migration algorithms that we propose. The experiments exhibit that the genetic algorithm, outperforms the other migration algorithms in searching for a migration sequence. When properly deployed, about a migration of 40% of routers reaps most of the benefit.

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