Randomized Local Fast Rerouting for Datacenter Networks with Almost Optimal Congestion

TL;DR

This paper introduces a randomized local rerouting algorithm for Clos datacenter networks that achieves near-optimal congestion under multiple link failures, ensuring high availability and resilience.

Contribution

It proposes a novel decentralized rerouting method for Clos networks that guarantees low congestion with limited local failure information.

Findings

Achieves asymptotically minimal congestion under bounded failures.

Provides theoretical bounds and guarantees for rerouting performance.

Validates effectiveness through rigorous analysis and proofs.

Abstract

To ensure high availability, datacenter networks must rely on local fast rerouting mechanisms that allow routers to quickly react to link failures, in a fully decentralized manner. However, configuring these mechanisms to provide a high resilience against multiple failures while avoiding congestion along failover routes is algorithmically challenging, as the rerouting rules can only depend on local failure information and must be defined ahead of time. This paper presents a randomized local fast rerouting algorithm for Clos networks, the predominant datacenter topologies. Given a graph $G=(V,E)$ describing a Clos topology, our algorithm defines local routing rules for each node $v\in V$, which only depend on the packet's destination and are conditioned on the incident link failures. We prove that as long as number of failures at each node does not exceed a certain bound, our algorithm achieves an asymptotically minimal congestion up to polyloglog factors along failover paths. Our lower bounds are developed under some natural routing assumptions.