A Hierarchical, Scalable Approach for Availability Analysis of Software Defined Networks

Software-Defined Networking (SDN) separates the network control and data planes in communication networks, thereby enabling the dynamic reconfiguration of the data plane at run-time through the control plane software. SDNs can be large, comprising of tens of controllers and thousands of switches, where combinatorial models for availability analysis can lead to state space explosion. Further complicating matters, the logically centralized SDN control plane is realized in practice in a distributed fashion to provide horizontal scale-out and redundancy to avoid a single point of failure. This distribution necessitates the use of consensus mechanisms to ensure consistency on key data in the context of failures, introducing further considerations into SDN models. To this end, we present the first hierarchical analytical model of SDN availability, under control and data plane failures, that takes consistency and recovery into account, and that is scalable. Our experiments using this model demonstrate the interplay between characteristics of the distributed control plane and data plane in overall network availability.