Bonsai: Efficient Fast Failover Routing Using Small Arborescences

Abstract

To provide high availability despite link failures, many modern communication networks feature fast failover mechanisms in the data plane, which operates orders of magnitude faster than the control plane. While the configuration of highly resilient data planes using the shortest possible backup routes is known to be a difficult combinatorial problem, over the last years, much progress has been made in the design of algorithms which provably guarantee connectivity even under many concurrent link failures. However, while these algorithms provide connectivity, the resulting routes after failures can be very long, which in turn can harm performance. In this paper, we propose, analyze, and evaluate methods for fast failover algorithms which account for the quality of the routes after failures, in addition to connectivity. In particular, we revisit the existing approach to cover the to-be-protected network with arc-disjoint spanning arborescences to define alternative routes to the destination, aiming to keep the stretch imposed by these trees low (hence the name of our method: Bonsai). We show that the underlying problem is NP-hard on general topologies and present lower bound results that are tight for various topologies, for any class of fast failover algorithms. We also present heuristics for general networks and demonstrate their performance benefits in extensive simulations. Finally, we show that failover algorithms using low-stretch arborescences, as a side effect, can provide connectivity under more general failure models than usually considered in the literature.

Distributed Consistent Network Updates in SDNs: Local Verification for Global Guarantees

“…For destination-based routing, observe that we do not need to forward to a node with a depth exactly one smaller, but any smaller depth (or higher version) would suffice. In this context, fault-tolerance could benefit benefit from link-disjoint forwarding trees [15], which can be computed efficiently [16], along with appropriate optimization for route lengths [17,18].…”

Improved Fast Rerouting Using Postprocessing

“…. Example network from [14] with two different t-rooted arc-disjoint spanning arborescence decompositions, T 1 left and T 2 right. In both of them one arborescence is drawn with dotted red arrows, while the second arborescence is depicted with dashed blue arrows.…”

“…hold when swapping e = (u, v) ∈ 0 − arborescence with e = (u, v ) ∈ E(T j ) to ensure that the resulting arborescences are valid [14]:…”

A Survey of Fast Recovery Mechanisms in the Data Plane

“…31), introducing latency and load. The latter has been addressed in a line of work by Pignolet et al [260], [261], e.g., relying on combinatorial designs or postprocessing of the arborescences [262]- [264].…”

“…Consequently, they may not provide any guarantees regarding the observed path length (or stretch). However, the recent advancements in static fast-recovery mechanisms relying on modified arborescence-based network decompositions provide one of the possible solutions to this issue [262], [269]. • Load: Another important objective is to avoid congestion during and after failover, see e.g., [260], [270].…”