Kaki: Concurrent Update Synthesis for Regular Policies via Petri Games

Abstract

Modern computer networks are becoming increasingly complex and for dependability reasons require frequent configuration changes. It is essential that forwarding policies are preserved not only before and after the configuration update but also at any moment during the inherently distributed execution of the update. We present Kaki, a Petri game based approach for automatic synthesis of switch batches that can be updated in parallel without violating a given (regular) forwarding policy like waypointing and service chaining. Kaki guarantees to find the minimum number of concurrent batches and it supports both splittable and nonsplittable flow forwarding. In order to achieve an optimal performance, we introduce two novel optimization techniques based on static analysis: decomposition into independent subproblems and identification of switches that can be collectively updated in the same batch. These techniques considerably improve the performance of our tool, relying on TAPAAL’s verification engine for Petri games as its backend. Experiments on a large benchmark of real networks from the topology Zoo database demonstrate that Kaki outperforms the state-of-the-art tool FLIP as it provides shorter (and provably optimal) concurrent update sequences at similar runtime.