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Detecting and Mitigating Abnormal Events in Large Scale Networks:Budget Constrained Placement on Smart Grids

机译:在大规模网络中检测和减轻异常事件:智能电网上的预算约束

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Several scenarios exist in the modern inter-connected world which call for an efficient neiwork in-terdiction algorithm. Applications are varied, -includ-ing various monitoring and load shedding applications on large smart energy grids, computer network security, preventing the spread, of Internet worms ad malware, policing international smuggling networks, and controlling the spread of diseases. In this paper we, consider some natural network optimization questions related to the budget constrained interdiction problem over general graphs, specifically focusing on the sensor/switch placement problem for large-scale energy grids. Many of these questions turn out to be computationally hard to tackle. We present a particular form of the interdiction question which is practically relevant and which we show as computationally tractable. A polynomial-time algorithm will be presented for solving this problem.
机译:现代连接世界中存在若干场景,呼吁高效的Neiwork in-Terdiction算法。应用程序变化, - 在大型智能能量网格,计算机网络安全,防止互联网蠕虫的广告恶意软件,监管国际走私网络,控制疾病传播的各种监测和负载脱落应用。在本文中,考虑与一般图表的预算受限互联问题有关的一些自然网络优化问题,专门针对大规模能量网格的传感器/开关放置问题。许多这些问题都会被计算地难以解决。我们提出了一种特定形式的互动问题,其实际上是相关的,我们作为计算贸易展示。将提出多项式时间算法来解决这个问题。

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