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http://dx.doi.org/10.3837/tiis.2021.07.016

Traffic Engineering with Segment Routing under Uncertain Failures  

Zheng, Zengwei (School of Computer & Computing Science, Zhejiang University City College)
Zhao, Chenwei (College of Computer Science & Technology, Zhejiang University)
Zhang, Jianwei (School of Computer & Computing Science, Zhejiang University City College)
Cai, Jianping (School of Computer & Computing Science, Zhejiang University City College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.7, 2021 , pp. 2589-2609 More about this Journal
Abstract
Segment routing (SR) is a highly implementable approach for traffic engineering (TE) with high flexibility, high scalability, and high stability, which can be established upon existing network infrastructure. Thus, when a network failure occurs, it can leverage the existing rerouting methods, such as rerouting based on Interior Gateway Protocol (IGP) and fast rerouting with loop-free alternates. To better exploit these features, we propose a high-performance and easy-to-deploy method SRUF (Segment Routing under Uncertain Failures). The method is inspired by the Value-at-Risk (VaR) theory in finance. Just as each investment risk is considered in financial investment, SRUF also considers each traffic distribution scheme's risk when forwarding traffic to achieve optimal traffic distribution. Specifically, SRUF takes into account that every link may fail and therefore has inherent robustness and high availability. Also, SRUF considers that a single link failure is a low-probability event; hence it can achieve high performance. We perform experiments on real topologies to validate the flexibility, high-availability, and load balancing of SRUF. The results show that when given an availability requirement, SRUF has greater load balancing performance under uncertain failures and that when given a demand requirement, SRUF can achieve higher availability.
Keywords
Segment Routing; Traffic Engineering; Value-at-Risk (VaR); Robustness; Uncertain Failures;
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