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Flexible Nodes Exclusion and Inclusion Capability Migration Model for Hybrid Software-Defined Network

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Abstract

Software-defined networking (SDN) is a popular network technology that enables flexible programmed network setup for optimizing network performance. However, the high cost of migrating existing devices to SDN leads to slow deployment particularly for large networks with thousands or more nodes. There are research works proposing methods for SDN migration under the total cost and budget but they lack the flexibility for network operator to set the specific budget in each time step for migration. Also, no research proposed a method for migrating a group of nodes that have a close relationship. Lastly, existing research also do not allow to set the node to be excluded from migration based on current network operation requirements. Therefore, we proposed a new hybrid software-defined network (Hybrid SDN) migration model that uses integer linear programming (ILP) formulation for calculating the migration nodes based on the user’s input dataset such as the number of nodes, the cost of nodes, the number of time step, the budget for each time step, the number of migration in certain time step, the nodes for U-pairs (a group of nodes that must be migrated together), and the nodes to be excluded from migration. This new model supports practical SDN migration that allows a group of nodes to be migrated together under flexible budget at each time step.

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Authors and Affiliations

  1. Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, 63100, Cyberjaya, Selangor, Malaysia

    Guo Xiong Tng, Saw Chin Tan, Neoh Kin Lin & Siew Hong Wei

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  1. Guo Xiong Tng
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  2. Saw Chin Tan
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  3. Neoh Kin Lin
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  4. Siew Hong Wei
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Correspondence to Saw Chin Tan.

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The authors declare that they have no conflicts of interest.

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Guo Xiong Tng, Tan, S.C., Lin, N.K. et al. Flexible Nodes Exclusion and Inclusion Capability Migration Model for Hybrid Software-Defined Network. Aut. Control Comp. Sci. 57, 577–588 (2023). https://doi.org/10.3103/S0146411623060111

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  • DOI: https://doi.org/10.3103/S0146411623060111

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