Efficient Recovery Path Computation for Fast Reroute in Large-scale Software Defined Networks

Abstract : With an increasing demand for resilience in software-defined networks (SDN), it becomes critical to minimize service recovery delay upon route failures. Fast reroute (FRR) mechanisms are widely used in IP and MPLS networks by computing the recovery path before a failure occurs. The centralized control plane in SDN can potentially enhance path computation, so that FRR path computation can better scale in SDN than in traditional networks. However, traditional FRR path computation algorithms could lead to poor performance in large-scale SDN. The problem can become more severe for a highly dynamic network, which often sees dozens of failures or configuration changes in any single day. We propose a new algorithm that exploits pruned searching to quickly compute recovery paths for all-pair switches/hosts upon a link failure. For applications requiring stringent path robustness levels, we also extend this algorithm to quickly find the shortest guaranteed-cost path, which ensures that the recovery path used upon on-path link failures has the minimum cost. Compared with traditional solutions, our evaluations show that our algorithm is about 8 ∼ 81 times faster than the practical implementation, 1.93 ∼ 3.11 times faster than the state-of-the-art solution. Our results also show that the shortest guaranteed-cost path can reduce the cost of the recovery path significantly. Moreover, we design a prototype to show how to deploy our algorithm in an OpenFlow network.
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Submitted on : Thursday, July 11, 2019 - 8:54:25 PM
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Kun Qiu, Jin Zhao, Xin Wang, Xiaoming Fu, Stefano Secci. Efficient Recovery Path Computation for Fast Reroute in Large-scale Software Defined Networks. IEEE Journal on Selected Areas in Communications, Institute of Electrical and Electronics Engineers, 2019, 37 (8), pp.1755-1768. ⟨10.1109/JSAC.2019.2927098⟩. ⟨hal-02181090⟩

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