Pinning complex dynamical networks with local betweenness centrality information

In this paper, we propose a local-betweenness-centrality (LBC)-based pinning strategy to stabilize undirected complex networked systems. Through two kinds of static real-world networks, the UAS airline routing map and the protein-protein interaction network, we show that the LBC-based pinning strategy, which only using the local information around the first and second neighbors of a focal vertex, can obtain the similar pinning efficiency with the betweenness-centrality (BC)-based pinning strategy that containing the global information of vertices´ traffic flow. Furthermore, for the evolving network, the AS-level Internet topology, we find that when the sampling period is short (such as every half a month), the LBC-based pinning strategy is better than the degree-based and BC-based pinning strategies, however, as the sampling period enlarges, the former scheme is inefficient.