Adaptive State Consistency for Distributed ONOS Controllers

Logically-centralized but physically-distributed SDN controllers are mainly used in large-scale SDN networks for scalability, performance and reliability reasons. These controllers host various applications that have different requirements in terms of performance, availability and consistency. Current SDN controller platform designs employ conventional strong consistency models so that the SDN applications running on top of the distributed controllers can benefit from strong consistency guarantees for network state updates. However, in large-scale deployments, ensuring strong consistency is usually achieved at the cost of generating performance overheads and limiting system availability. That makes weaker optimistic consistency models such as the eventual consistency model more attractive for SDN controller platform applications with high-availability and scalability requirements. In this paper, we argue that the use of the standard eventual consistency models, though a necessity for efficient scalability in modern SDN systems, provides no bounds on the state inconsistencies tolerated by the SDN applications. To remedy that, we propose an adaptive consistency model for the distributed ONOS controllers following the notion of continuous and compulsory (per-controller) eventual consistency, where network application states adapt their eventual consistency level dynamically at run-time based on the observed state inconsistencies under changing network conditions. When compared to the ONOS approach to static eventual consistency, our approach proved efficient in minimizing state synchronization overheads while taking into account application state consistency SLAs and without compromising the application requirements of high-availability, in the context of large-scale SDN networks.