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Measuring the Control-Data Plane Consistency in Software Defined Networking

机译:测量软件定义网络中的控制数据平面一致性

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Software Defined Networking (SDN) simplifies network management by separating the control plane from the data plane in performance networks. However, the actual packet behaviors, conforming to the rules in the data plane flow tables, may violate the original policies in the controller due to the inconsistency between the data plane and control plane. To address this problem, we propose 2MVeri, a new framework for measuring the control-data plane consistency, defined as the consistency between the control plane policies and data plane rules. 2MVeri uses a Bloom filter and a two-dimensional vector as a tag which is inserted in the packet header and is updated in each switch that the packet traverses. By exploiting path information compressed in the tag, 2MVeri can verify the control-data plane consistency. Moreover, when verification fails, 2MVeri can localize the faulty switch. Evaluations conducted on a datacenter network with the fat tree topology k=4 demonstrate that 2MVeri achieves 100% accuracy in consistency verification and high fault localization performance.
机译:软件定义的网络(SDN)通过将控制平面与性能网络中的数据平面分离来简化网络管理。然而,由于数据平面和控制平面之间的不一致,符合数据平面流量表中的规则,符合数据平面流量表中的规则的实际分组行为可能违反控制器中的原始策略。为了解决这个问题,我们提出了2mveri,一个用于测量控制数据平面一致性的新框架,定义为控制平面策略和数据平面规则之间的一致性。 2mveri使用绽放过滤器和二维向量作为插入分组标题的标记,并在数据包遍历的每个开关中更新。通过利用在标签中压缩的路径信息,2mveri可以验证控制数据平面一致性。此外,当验证失败时,2mveri可以本地化故障开关。在数据中心网络中进行的评估与脂肪树拓扑k = 4表明,2mveri在一致性验证和高故障定位性能中实现了100 %的准确性。

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