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Evader Interdiction and Collateral Damage

机译:规避拦截和附带损害

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In network interdiction problems, evaders (e.g., hostile agents or data packets) may be moving through a network towards targets and we wish to choose locations for sensors in order to intercept the evaders before they reach their destinations. The evaders might follow deterministic routes or Markov chains, or they may be reactive, i.e., able to change their routes in order to avoid sensors placed to detect them. The challenge in such problems is to choose sensor locations economically, balancing security gains with costs, including the inconvenience sensors inflict upon innocent travelers. We study the objectives of 1) maximizing the number of evaders captured when limited by a budget on sensing cost and 2) capturing all evaders as cheaply as possible. We give optimal sensor placement algorithms for several classes of special graphs and hardness and approximation results for general graphs, including for deterministic or Markov chain-based and reactive or oblivious evaders. In a similar-sounding but fundamentally different problem setting posed by [7] where both evaders and innocent travelers are reactive, we again give optimal algorithms for special cases and hardness and approximation results on general graphs.
机译:在网络拦截问题中,逃避者(例如,敌对代理或数据包)可能正在通过网络向目标移动,我们希望选择传感器的位置,以便在逃避者到达目的地之前对其进行拦截。逃避者可能遵循确定性路线或马尔可夫链,或者可能是反应性的,即能够更改其路线以避免避开用于检测它们的传感器。这些问题的挑战在于经济地选择传感器位置,在安全收益与成本之间取得平衡,包括给无辜旅行者造成的不便传感器。我们研究了以下目标:1)在受到传感成本预算的限制时,最大限度地捕获逃避者; 2)尽可能便宜地捕获所有逃避者。我们为几种特殊图形提供了最佳的传感器放置算法,并为一般图形提供了硬度和近似结果,包括确定性或基于马尔可夫链的,反应性或遗忘的逃避者。在[7]听起来相似但根本不同的问题中,逃避者和无辜旅行者都具有反应性,我们再次针对特殊情况和硬度,在一般图表上给出了最佳算法。

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