ADD: Application and Data-Driven Controller Design

Existing SDN controllers commonly adopt an event-driven model that minimizes southbound communication and control-plane overhead. This model satisfies most existing SDN applications' goals to maximize data plane performance while still being able to programmatically control with a decent level of visibility. However, as network composition becomes more heterogeneous with NFV and IoT, such model can be insufficient for future applications that rely more on data analysis and intelligent decision making. In this paper, we present our findings in a case study on smart manufacturing systems, which have highly heterogeneous device compositions, and applications that are much less "throughput" hungry or "latency" sensitive than network applications but require a lot more data for (real-time) decision making. We share the insights we gain that help us design a new Application and Data-Driven (ADD) model for SDN controllers. We build a proof-of-concept ADD controller based on this model and develop two applications to showcase its new capabilities. Evaluation results show that ADD delivers satisfying scalability and performance. More importantly, applications enabled by ADD gain more insights of the data plane and can make better decisions faster.