使用连通性映射映射网络状态
Mapping Network States Using Connectivity Queries
摘要：
我们是否可以从供应节点的可达节点样本中推断出基础设施网络的所有故障组件？自然灾害发生后，最关键的中断后流程之一是快速确定关键基础设施组件的损坏或故障状态。然而，考虑到在破坏性事件之后通常只有一小部分组件可以访问或观察到，这是不平凡的。过去的工作已经考虑到推断失败的组件给定的点探针，即与失败的组件的直接样本。相比之下，我们研究了更难的问题，推断失败的组件部分信息的一些“可服务的”可达节点和一个小样本的点探针，是第一个往往更实际的获得。我们用最小描述长度（MDL）的原则，制定这个新的问题，然后提出了一个贪心算法，最小化MDL成本有效。我们评估我们的算法在地震后的真实网络的域专家模拟。我们的算法成功地识别故障组件，特别是影响整个系统性能的关键组件。
英文摘要：
Can we infer all the failed components of an infrastructure network, given a sample of reachable nodes from supply nodes? One of the most critical post-disruption processes after a natural disaster is to quickly determine the damage or failure states of critical infrastructure components. However, this is non-trivial, considering that often only a fraction of components may be accessible or observable after a disruptive event. Past work has looked into inferring failed components given point probes, i.e. with a direct sample of failed components. In contrast, we study the harder problem of inferring failed components given partial information of some `serviceable' reachable nodes and a small sample of point probes, being the first often more practical to obtain. We formulate this novel problem using the Minimum Description Length (MDL) principle, and then present a greedy algorithm that minimizes MDL cost effectively. We evaluate our algorithm on domain-expert simulations of real networks in the aftermath of an earthquake. Our algorithm successfully identify failed components, especially the critical ones affecting the overall system performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
