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Load-Optimal Local Fast Rerouting for Resilient Networks

机译:弹性网络的负载优化本地快速重路由

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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.
机译:可靠且高度可用的计算机网络必须实现有弹性的快速重新路由机制:在链路或节点发生故障时,可以快速确定替代路由,而无需涉及网络控制平面。然而,设计这样的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,即提前安装故障转移规则,而无需知道运行时实际发生的故障。实际上,对于弹性路由算法的设计,目前知之甚少。本文提出了一种确定性的本地故障转移机制,我们证明了该机制可在各种通信模式下实现最小的网络负载,从而解决一个开放性问题。我们的机制依赖于关键见解,即弹性路由本质上构成了无需协调的分布式算法。因此,我们以组合设计理论为基础,并基于对称块设计理论开发了一种新颖的确定性故障转移机制,该机制可以容忍n节点网络和最坏情况下最大数量的Ω(n)链路故障,而始终确保路由连接。特别是,我们表明至少需要Ω(Φ2)个链路故障才能生成至少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的现有限制相匹配。我们通过模拟对形式分析进行补充,这表明我们的方法不仅在最坏的情况下还优于以前的方案。

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