Toward consistent state management of adaptive programmable networks based on P4

Emerging network applications (augmented reality, industrial Internet, etc.) introduce stringent new requirements on the performance, dependability, and adaptability of communication networks. Programmable data planes (e.g., based on P4) provide new opportunities to meet these requirements, by enabling adaptive network reconfigurations. However, ensuring consistency during such reconfigurations remains challenging. This paper makes a first step toward a more automated state management of adaptive data planes. In particular, we present an efficient P4 state management framework, P4State, which allows to quickly identify the network states from the source code that are critical for data plane reconfigurations (e.g., due to scaling, failure recovery). We report on first promising evaluation results of our prototype implementation in terms of correctness and efficiency, also considering two case studies using HULA (load balancing in data center) and HashPipe (line-rate measurement in data plane).