Optimal state replication in stateful data planes

TL;DR

This paper addresses the challenge of optimally placing replicated states in SDN data planes to improve network responsiveness and coherence, proposing an approximation algorithm and analyzing the optimal number of replicas.

Contribution

It formulates the optimal placement problem for replicated states considering traffic routing and synchronization, and introduces a scalable approximation algorithm with asymptotic analysis.

Findings

The approximation algorithm closely matches the optimal solution.

Replicating states improves network performance over single-replica setups.

Asymptotic analysis determines the optimal number of state replicas.

Abstract

In SDN stateful data planes, switches can execute algorithms to process traffic based on local states. This approach permits to offload decisions from the controller to the switches, thus to reduce the latency to react to network events. We consider distributed network applications that process traffic at each switch based on local replicas of network-wide states. Replicating a state across multiple switches poses many challenges, because the number of state replicas and their placement affects both the data traffic and the synchronization traffic among the replicas. In our work, we formulate the optimal placement problem for replicated states, taking into account the data traffic routing, to ensure that the network applications affect the proper traffic flows, and the synchronization traffic between replicas, to ensure state coherence. Due to the high complexity required to find the optimal solution, we propose an approximated algorithm able to scale to large network instances. We show numerically that this algorithm, despite its simplicity, approximates quite well the optimal solution. We also show the beneficial effects of replicating the states with respect to the single-replica scenario, so far considered in the literature. Finally, we provide an asymptotic analysis to find the optimal number of replicas.