Load-Optimal Local Fast Rerouting for Resilient Networks

Y. Pignolet, S. Schmid, Gilles Trédan
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引用次数: 16

Abstract

Reliable and highly available computer networks must implement resilient fast rerouting mechanisms: upon a link or node failure, an alternative route is determined quickly, without involving the network control plane. Designing such fast failover mechanisms capable of dealing with multiple concurrent failures however is challenging, as failover rules need to be installed proactively, i.e., ahead of time, without knowledge of the actual failures happening at runtime. Indeed, only little is known today about the design of resilient routing algorithms. This paper presents a deterministic local failover mechanism which we prove to result in a minimum network load for a wide range of communication patterns, solving an open problem. Our mechanism relies on the key insight that resilient routing essentially constitutes a distributed algorithm without coordination. Accordingly, we build upon the theory of combinatorial designs and develop a novel deterministic failover mechanism based on symmetric block design theory which tolerates a maximal number of Ω(n) link failures in an n-node network and in the worst-case, while always ensuring routing connectivity. In particular, we show that at least Ω(ϕ2) link failures are needed to generate a maximum link load of at least ϕ, which matches an existing bound on the number of link failures needed for an optimal failover scheme. We complement our formal analysis with simulations, showing that our approach outperforms prior schemes not only in the worst-case.
弹性网络的负载最优本地快速重路由
可靠和高可用性的计算机网络必须实现弹性快速重路由机制:当链路或节点故障时,快速确定替代路由,而不涉及网络控制平面。然而,设计这种能够处理多个并发故障的快速故障转移机制是具有挑战性的,因为需要主动安装故障转移规则,即提前安装,而不需要了解运行时发生的实际故障。事实上,目前对弹性路由算法的设计知之甚少。本文提出了一种确定性的本地故障转移机制,并证明该机制可以在各种通信模式下产生最小的网络负载,从而解决了一个开放性问题。我们的机制依赖于一个关键的洞察力,即弹性路由本质上构成了一个没有协调的分布式算法。因此,我们在组合设计理论的基础上,开发了一种基于对称块设计理论的新型确定性故障转移机制,该机制在n节点网络和最坏情况下允许最大数量的Ω(n)链路故障,同时始终确保路由连通性。特别是,我们表明至少Ω(ϕ2)链路故障需要产生至少φ的最大链路负载,这与最佳故障转移方案所需的链路故障数量的现有界限相匹配。我们用模拟来补充我们的形式分析,表明我们的方法不仅在最坏情况下优于先前的方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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