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Problem Localization and Quantification Using Formal Evidential Reasoning for Virtual Networks

机译:虚拟网络使用形式证据推理的问题定位和量化

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摘要

Overlay (virtual) networks are mainly used to improve Internet reliability and facilitate a rapid deployment of new services. However, in order for overlay services to adapt to dynamic network conditions in a timely manner, efficient diagnosis of performance problems is required. Existing overlay diagnosis approaches assume extensive knowledge about the network and require invasive monitoring sensors or active measurements. In this paper, we propose a novel diagnosis technique to localize performance anomalies and determine the packet loss in each network component. Our approach is purely based on packet loss observations at the end-points to reason about the loss location and severity in the network without any active probing or sensor deployment. We formulate the problem as a constraint-satisfaction problem using network loss properties and end-user observations. Our diagnosis is robust against insufficient observations or malicious end-user participation. We evaluate our approach extensively using simulation and experimentation and demonstrate the accuracy, effectiveness, and scalability of our approach under various network sizes, participation ratio, and malicious observation ratio.
机译:覆盖(虚拟)网络主要用于提高Internet可靠性并促进新服务的快速部署。但是,为了使覆盖服务能够及时适应动态网络状况,需要对性能问题进行有效的诊断。现有的覆盖层诊断方法假定您具有有关网络的广泛知识,并且需要侵入式监视传感器或主动测量。在本文中,我们提出了一种新颖的诊断技术来定位性能异常并确定每个网络组件中的数据包丢失。我们的方法完全基于端点上的数据包丢失观察,无需任何主动探测或部署传感器即可推断出网络中的丢失位置和严重性。我们使用网络丢失属性和最终用户观察将问题表述为约束满足问题。我们的诊断对观察不足或最终用户的恶意参与是有力的。我们通过仿真和实验对我们的方法进行了广泛的评估,并证明了在各种网络规模,参与率和恶意观察率下,该方法的准确性,有效性和可扩展性。

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