ECOTE: Priority-Aware Optical Restoration for WAN Traffic Engineering
Yiren Zhao, Kunling He, Zhiquan Wang, Ran Shu, Jilong Wang, Congcong Miao
摘要
Fiber cuts are among the most common and disruptive failures in cloud networks. They can prevent cloud providers from maintaining committed service availability, causing Service Level Agreement (SLA) violations that directly translate into monetary penalties. Existing traffic engineering (TE) approaches enhance failure resilience, and recent systems further incorporate optical restoration to recover lost bandwidth after failures. However, they still treat services largely uniformly and optimize primarily for network throughput rather than the economic impact of heterogeneous SLA penalties. In this paper, we present ECOTE, the first priority-aware TE system with optical restoration that explicitly minimizes revenue loss. Specifically, ECOTE introduces a new optical restoration formulation with a dedicated capacity restoration solver to compute an optimal restoration plan that maximizes restorable capacity under physical constraints. ECOTE also designs a priority-aware TE algorithm that allocates the restored bandwidth capacity according to SLA penalties, thereby reducing monetary cost. We evaluate ECOTE using a production-level WAN testbed and through large-scale simulations. The testbed evaluation demonstrates ECOTE achieves zero loss for high-priority services and more than 10× revenue loss reduction compared to state-of-the-art. Our large-scale simulation results show that ECOTE can support at least 2.5× and 2.0× more demand for different high priority services compared to the state-of-the-art solutions. Meanwhile, ECOTE reduces the revenue loss by at least an order of magnitude less than existing solutions.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- ARROW: restoration-aware traffic engineeringZhizhen Zhong, Manya Ghobadi, Alaa Khaddaj, Jonathan Leach 等SIGCOMM 2021 · 被引用 37 次
- PreTE: Traffic Engineering with Predictive FailuresCongcong Miao, Zhizhen Zhong, Yiren Zhao, Arpit Gupta 等SIGCOMM 2025 · 被引用 6 次
- ARES: Predictable Traffic Engineering under Controller Failures in SD-WANsSongshi Dou, Li Qi, Zehua GuoWWW 2024 · 被引用 4 次
- Dynamic Learning-based Link Restoration in Traffic Engineering with ArchieWenlong Ding, Hong XuINFOCOM 2024 · 被引用 2 次
- Cost-effective Cloud Edge Traffic Engineering with CascaraRachee Singh, Sharad Agarwal, Matt Calder, Paramvir BahlNSDI 2021 · 被引用 79 次
