Simplifying Flow Updates in Software-Defined Networks Using Atoman

Abstract

Flow updates are common in today's networks, and software-defined networking (SDN) enables network operators to reconfigure switches for updating flows easily. However, the implementation of flow updates requires to meet many different expectations regarding consistency, resource constraints, and performance. To carry updates out as intended, network operators often need to spend significant effort in update management, developing complex network optimizations and customized heuristics on a case-by-case basis. In this paper, we strive to simplify the flow updates in SDN networks. To this end, we present \mathsf{Atoman} , a framework that uses high-level abstractions to capture various update intents and formulates flow updates problems as segment-based update scheduling optimizations to obtain satisfied update solutions. The captured update intents are translated into constraints and objectives of update scheduling optimizations. By extracting critical updating flows and employing decomposition techniques, \mathsf{Atoman} can efficiently reduce the scale of problems in each solving and generate near-optimal update solutions. We conduct extensive simulations to evaluate \mathsf{Atoman} and the simulation results show that \mathsf{Atoman} significantly saves operator efforts in managing flow updates and provides comparable or better efficiency than prior customized solutions.