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On the Entity Hardening Problem in multi-layered interdependent networks

机译:多层相互依赖网络中的实体强化问题

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The power grid and the communication network are highly interdependent on each other for their well being. In recent times the research community has shown significant interest in modeling such interdependent networks and studying the impact of failures on these networks. Although a number of models have been proposed, many of them are simplistic in nature and fail to capture the complex interdependencies that exist between the entities of these networks. To overcome the limitations, recently an Implicative Interdependency Model that utilizes Boolean Logic, was proposed and a number of problems were studied. In this paper we study the “entity hardening” problem, where by “entity hardening” we imply the ability of the network operator to ensure that an adversary (be it Nature or human) cannot take a network entity from operative to inoperative state. Given that the network operator with a limited budget can only harden k entities, the goal of the entity hardening problem is to identify the set of k entities whose hardening will ensure maximum benefit for the operator, i.e. maximally reduce the ability of the adversary to degrade the network. We classify the problem into four cases and show that the problem is solvable in polynomial time for the first case, whereas for others it is NP-complete. We provide an inapproximability result for the second case, an approximation algorithm for the third case, and a heuristic for the fourth (general) case. We evaluate the efficacy of our heuristic using power and communication network data of Maricopa County, Arizona. The experiments show that our heuristic almost always produces near optimal results.
机译:电网和通信网络彼此之间高度相互依存。近年来,研究界对建模此类相互依赖的网络以及研究故障对这些网络的影响表现出了极大的兴趣。尽管已经提出了许多模型,但是其中许多模型本质上都是简单的,无法捕获这些网络的实体之间存在的复杂的相互依赖性。为了克服这些限制,最近提出了一种利用布尔逻辑的隐含相互依赖模型,并对许多问题进行了研究。在本文中,我们研究“实体强化”问题,其中通过“实体强化”暗示网络运营商确保对手(无论是自然人还是人)不能将网络实体从有效状态转移到无效状态的能力。假设预算有限的网络运营商只能加固k个实体,则实体加固问题的目标是确定k个实体,其加固将确保为运营商带来最大收益,即最大程度地降低对手降级的能力网络。我们将问题分为四种情况,并表明对于第一种情况,该问题在多项式时间内是可解决的,而对于其他情况,它是NP完全的。我们为第二种情况提供了不可逼近的结果,为第三种情况提供了近似算法,并为第四种(一般)情况提供了启发式方法。我们使用亚利桑那州马里科帕县的电力和通讯网络数据评估启发式方法的有效性。实验表明,我们的启发式方法几乎总是产生接近最佳的结果。

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