缓解复杂网络级联故障的简化方法

Karan Singh, V. K. Chandrasekar, D. V. Senthilkumar
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引用次数: 0

摘要

级联故障是对复杂系统完整性的根本性威胁,往往会导致各种基础设施和金融网络的全面崩溃。本研究阐述了一种稳健而实用的方法,旨在降低复杂网络中发生此类故障的风险,强调本地网络拓扑结构的关键作用。我们策略的核心是一种创新算法,它能系统地识别网络中的关键节点子集,这个子集的相对规模在整个网络中非常重要。为了增强这种算法,我们采用了一种图着色启发式,以精确地隔离最重要的节点,从而在最大限度地提高战略价值的同时,最小化子集的规模。确保这些节点的安全大大增强了网络抵御级联故障的能力。所提出的识别关键节点的方法和实验结果表明,所提出的技术在识别关键节点方面优于其他典型技术。我们通过与现有缓解策略的对比分析,证实了我们的方法的优越性,并评估了它在各种网络配置和故障情况下的性能。通过将我们的方法应用到真实世界的网络中,提供了经验验证,证实了它作为增强网络鲁棒性的战略工具的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Streamlined approach to mitigation of cascading failure in complex networks
Cascading failures represent a fundamental threat to the integrity of complex systems, often precipitating a comprehensive collapse across diverse infrastructures and financial networks. This research articulates a robust and pragmatic approach designed to attenuate the risk of such failures within complex networks, emphasizing the pivotal role of local network topology. The core of our strategy is an innovative algorithm that systematically identifies a subset of critical nodes within the network, a subset whose relative size is substantial in the context of the network's entirety. Enhancing this algorithm, we employ a graph coloring heuristic to precisely isolate nodes of paramount importance, thereby minimizing the subset size while maximizing strategic value. Securing these nodes significantly bolsters network resilience against cascading failures. The method proposed to identify critical nodes and experimental results show that the proposed technique outperforms other typical techniques in identifying critical nodes. We substantiate the superiority of our approach through comparative analyses with existing mitigation strategies and evaluate its performance across various network configurations and failure scenarios. Empirical validation is provided via the application of our method to real-world networks, confirming its potential as a strategic tool in enhancing network robustness.
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