Resilient Control Plane Design for Virtual Software Defined Networks

Control plane survivability in virtual software-defined networks (vSDN) - where multiple tenants share the same physical infrastructure - is even more critical than in normal SDN networks. A reliable communication channel from the switches through the network hypervisor to the virtual controller is inevitable in order to avoid state inconsistencies, tenant isolation and security issues on the virtual switches. Although reliable controller placement and control plane design was thoroughly investigated in SDNs, there was a lack of attention for resilient hypervisor placement and control path design for vSDNs. Therefore, in this paper we make a two-fold contribution towards a survivable vSDN control plane. First, we propose an approximation algorithm for (hypervisor) placement which - in contrast with traditional approaches which minimize the average latency to the hypervisors as an objective function - focuses on finding the appropriate number of hypervisor instances to satisfy the control path length constraints declared in the service level agreements, leaving enough options open for self-driving network designs and intelligent algorithms. Second, we propose a general dynamic program that calculates minimum length paths traversing specific type of nodes in a given order, and apply it to find control paths from the virtual controller of the slice to the virtual switches traversing the corresponding hypervisor location. We conduct thorough simulations on real-world topologies to demonstrate the effectiveness of our approaches in no failure and single link failure scenarios.

Automated summary

This paper focuses on the survivability of the control plane in virtual software-defined networks (vSDN) and proposes two contributions: an approximation algorithm for hypervisor placement and a general dynamic program for calculating minimum length paths. Thorough simulations on real-world topologies demonstrate the effectiveness of the proposed approaches in different scenarios.