Optimization Models for Flexible and Adaptive SDN Network Virtualization Layers

TL;DR

This paper studies how to optimize the reconfiguration of SDN network virtualization layers to balance performance and flexibility, using formal optimization models and simulations.

Contribution

It introduces formal mixed integer programming models for dynamic SDN virtualization layer reconfiguration, addressing multi-objective optimization challenges.

Findings

Pareto frontiers show trade-offs between latency and reconfiguration costs

Simulation results demonstrate the effectiveness of the proposed models

Initial analysis highlights the complexity of balancing objectives in SDN virtualization

Abstract

Network hypervisors provide the network virtualization layer for Software Defined Networking (SDN). They enable virtual network (VN) tenants to bring their SDN controllers to program their logical networks individually according to their demands. In order to make use of the high flexibility of virtual SDN networks and to provide high performance, the deployment of the virtualization layer needs to adapt to changing VN demands. This paper initializes the study of the optimization of dynamic SDN network virtualization layers. Based on the definition of reconfiguration events, we formalized mixed integer programs to analyze the multi-objective problem of adapting virtualization layers. Our initial simulation results demonstrate Pareto frontiers of conflicting objectives, namely control plane latency and hypervisor and control path reconfigurations.