Cost-location aware heuristic algorithm for hybrid SDN deployment


Software-Defined Networking (SDN) has gained tremendous attention in the past few years for its advantages over network controllability. Nonetheless, the deployment of SDN in legacy network is likely to span multi-periods over months or years for budget consideration. Network operators, especially for a network consists of thousand or more nodes, are eager to understand how legacy networks can be deploying gradually towards SDN with variety of constraints. The reliability of network should be the utmost concern during SDN deployment in legacy network. Primarily, node exclusion is essential in SDN deployment process as the exclusion of critical node during the process greatly improves network stability and reliability. Therefore, we propose a heuristic algorithm for multi-periods SDN node migration in legacy network with respect to node exclusion and budget. We first formulate the aforementioned problem in Integer Linear Programming (ILP) model, and we evaluate the proposed ILP model and our proposed heuristic algorithm with regard to solution quality and processing time. The results show that our proposed algorithm maintains its overall correctness with O(N2) polynomial time complexity. In addition to migration sequence computation, the results of our proposed algorithm reveal the impact of each node in SDN deployment as Key Node, Critical Node and Diminishing Return Analysis. These information offers better decision for network operator during hybrid SDN deployment. Ultimately, the results of our proposed algorithm offers valuable insight in which significantly reduce up to 83% of investment while reaping the most performance gain out of SDN deployment in legacy network.

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Correspondence to Tan Saw Chin.

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Wei, S.H., Chin, T.S. & Kwang, L.C. Cost-location aware heuristic algorithm for hybrid SDN deployment. Ann Math Artif Intell (2021).

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  • Software-defined networking
  • Heuristic algorithm
  • Hybrid SDN deployment
  • Integer linear programming