同步(交流)
稳健性(进化)
复杂网络
可扩展性
计算机科学
趋同(经济学)
启发式
分布式计算
钥匙(锁)
理论(学习稳定性)
数学优化
贪婪算法
复杂系统
局部最优
计算复杂性理论
生成树
节点(物理)
面子(社会学概念)
网络拓扑
网络动力学
控制(管理)
鲁棒控制
作者
Zhu Mao,Tianlong Fan,Linyuan Lü
标识
DOI:10.48550/arxiv.2504.00493
摘要
Synchronization is essential for the stability and coordinated operation of complex networked systems. Pinning control, which selectively controls a subset of nodes, provides a scalable solution to enhance network synchronizability. However, existing strategies face key limitations: heuristic centrality-based methods lack a direct connection to synchronization dynamics, while spectral approaches, though effective, are computationally intensive. To address these challenges, we propose a perturbation-based optimized strategy (PBO) that dynamically evaluates each node's spectral impact on the Laplacian matrix, achieving improved synchronizability with significantly reduced computational costs (with complexity O(kM)). Extensive experiments demonstrate that the proposed method outperforms traditional strategies in synchronizability, convergence rate, and pinning robustness to node failures. Notably, in all the empirical networks tested and some generated networks, PBO significantly outperforms the brute-force greedy strategy, demonstrating its ability to avoid local optima and adapt to complex connectivity patterns. Our study establishes the theoretical relationship between network synchronizability and convergence rate, offering new insights into efficient synchronization strategies for large-scale complex networks.
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