Quantifying entity criticality for fault impact analysis and dependability enhancement in software-defined networks
Song Huang, Zhiang Deng, Song Fu · 2016
Software-defined networking (SDN) empowers network operators with more flexibility to program their networks. With SDN, network management moves from codifying functionality in terms of low-level device configurations to building virtualized software entities that facilitate network management and debugging. By separating the complexity of state distribution from network specification, SDN provides new ways to solve existing routing problems while allowing the use of dependability techniques. However, the dependability of SDN itself is still an open issue. In this paper, we study the criticality of various entities in a virtualized network, which is important for analyzing the impact of component failures. We propose a network entity criticality framework with a set of models to quantify the importance of different entities for network dependability. We incorporate the topology information of entities in the calculation of their criticality. We validate the proposed models and evaluate their performance on two virtualized networks used in production environments. Our experimental results show that the proposed criticality models can achieve a high accuracy for quantifying the criticality of virtualized entities. In addition, the graph entropy criticality model and the PageRank criticality model scale well and can work for large-scale virtualized networks.