SDNRacer: concurrency analysis for software-defined networks

Ahmed El-Hassany, Jeremie Miserez, Pavol Bielik, L. Vanbever, Martin T. Vechev
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引用次数: 42

Abstract

Concurrency violations are an important source of bugs in Software-Defined Networks (SDN), often leading to policy or invariant violations. Unfortunately, concurrency violations are also notoriously difficult to avoid, detect and debug. This paper presents a novel approach and a tool, SDNRacer, for detecting concurrency violations of SDNs. Our approach is enabled by three key ingredients: (i) a precise happens- before model for SDNs that captures when events can happen concurrently; (ii) a set of sound, domain-specific filters that reduce reported violations by orders of magnitude, and; (iii) a sound and complete dynamic analyzer, based on the above, that can ensure the network is free of harmful errors such as data races and per-packet incoherence. We evaluated SDNRacer on several real-world OpenFlow controllers, running both reactive and proactive applications in large networks. We show that SDNRacer is practically effective: it quickly pinpoints harmful concurrency violations without overwhelming the user with false positives.
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SDNRacer:软件定义网络的并发分析
并发性违反是软件定义网络(SDN)中bug的一个重要来源,通常会导致策略或不变性违反。不幸的是,并发性冲突也非常难以避免、检测和调试。本文提出了一种检测sdn并发性违规的新方法和工具——SDNRacer。我们的方法由三个关键要素实现:(i)精确的sdn发生前模型,该模型捕获事件何时可以并发发生;(ii)一套健全的、特定于领域的过滤器,可按数量级减少所报告的违规行为;(iii)在上述基础上,一个健全和完整的动态分析器,可以确保网络没有有害的错误,如数据竞争和每包不相干。我们在几个真实的OpenFlow控制器上评估了SDNRacer,在大型网络中运行被动和主动应用程序。我们证明了snracer实际上是有效的:它可以快速确定有害的并发性违规,而不会让用户被误报淹没。
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