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Network Decontamination

机译:网络净化

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The Network Decontamination problem consists of coordinating a team of mobile agents in order to clean a contaminated network. The problem is actually equivalent to tracking and capturing an invisible and arbitrarily fast fugitive. This problem has natural applications in network security in computer science or in robotics for search or pursuit-evasion missions. Many different objectives have been studied: the main one being the minimization of the number of mobile agents necessary to clean a contaminated network. Many environments (continuous or discrete) have also been considered. In this Chapter, we focus on networks modeled by graphs. In this context, the optimization problem that consists of minimizing the number of agents has a deep graph-theoretical interpretation. Network decontamination and, more precisely, graph searching models, provide nice algorithmic interpretations of fundamental concepts in the Graph Minors theory by Robertson and Seymour. For all these reasons, graph searching variants have been widely studied since their introduction by Breish (1967) and mathematical formal-izations by Parsons (1978) and Petrov (1982). This chapter consists of an overview of the algorithmic results on graph decontamination and graph searching.
机译:网络除污问题包括协调一组移动代理以清理受污染的网络。问题实际上等同于跟踪和捕获不可见且任意快速的逃犯。这个问题在计算机科学或机器人技术中的网络安全性中具有自然应用,用于搜索或逃避任务。已经研究了许多不同的目标:主要目标是最大限度地减少清洁受污染网络所需的移动代理的数量。还考虑了许多环境(连续或离散)。在本章中,我们重点介绍由图建模的网络。在这种情况下,由最小化代理数量构成的优化问题具有深刻的图论解释。网络去污,更确切地说是图搜索模型,提供了Robertson和Seymour的Graph Minors理论中基本概念的很好的算法解释。由于所有这些原因,自从Breish(1967)引入图搜索变体以及Parsons(1978)和Petrov(1982)引入数学形式化以来,对图搜索变体进行了广泛的研究。本章概述了图形净化和图形搜索的算法结果。

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