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Multi-domain virtual network embedding with dynamic flow migration in software-defined networks
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DOI：10.1016/j.jnca.2020.102639.png)
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Software Defined Networking (SDN) decouples the control and data planes of a network, and employs a central controller to provide effective use of network resources and ease of service provision. Virtualization in SDN empowers the virtual SDN networks to share common physical network infrastructures, and, thus, make them capable for versatile service provisioning. In such setting, SDN hypervisor supports multiple virtual SDN network (vSDN) in which each vSDN has its own controller. To create virtual networks and achieving optimal sharing of physical network resources, virtual network embedding (VNE) algorithms are designed. Single domain VNE is a well-studied problem in NV literature. However, in most of the real life scenarios, VNs are provisioned across heterogeneous administrative domains belonging to different Infrastructure Providers (InPs). In this paper, we propose a VNE algorithm, namely vSDN-CLA, using Irregular Cellular Learning Automata (ICLA) for multi-domain SDN networks. We consider two aspects - optimal mapping of virtual nodes and links into multi-domain substrate network, and optimal placement of SDN controller with respect to throughput and end-to-end delay. We extend the vSDN-CLA by considering dynamic flow migration to achieve resource optimal routing. We evaluate the proposed schemes using Mininet We observe that the proposed schemes outperform the existing benchmark schemes with respect to throughput, end-to-end delay, and virtual network request acceptance ratio under both the single and multi-domain environments.
Keyword:
Virtual network embedding
Software defined networking
Multi-domain SDN
Cellular learning automata
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