2012Unpublished venueRequires access

Optimizing Method for Synchronization of Small-World Networks

Xiaoying Hu, Weiguo Liu, Rongli Guo, Tuan Guo

Open publisher page 1 citations

Abstract

A novel optimizing technique for small-world network model is proposed and demonstrated. The effects of the key parameters to the synchronization of complex networks are investigated theoretically, including the characteristic path length, distribution degree, clustering coefficient and betweenness. It is found that the networks present a significant synchronization different with the equal characteristic path length and clustering coefficient. Simulation results show that neither the characteristic path length nor the clustering coefficient of complex networks can independently demonstrate the synchronization of the complex network. The heterogeneity of the distribution degree essentially suppresses the synchronization of complex networks, while the maximal betweenness is an effective indicator for synchronizability.

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What this paper is about

A novel optimizing technique for small-world network model is proposed and demonstrated. The effects of the key parameters to the synchronization of complex networks are investigated theoretically, including the characteristic path length, distribution degree, clustering coefficient and betweenness. It is found that the networks present a significant synchronization different with the equal characteristic path length and clustering coefficient. Simulation results show that neither the characteristic path length nor the clustering coefficient of complex networks can independently demonstrate the synchronization of the complex network. The heterogeneity of the distribution degree essentially suppresses the synchronization of complex networks, while the maximal betweenness is an effective indicator for synchronizability.

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Available abstract

A novel optimizing technique for small-world network model is proposed and demonstrated. The effects of the key parameters to the synchronization of complex networks are investigated theoretically, including the characteristic path length, distribution degree, clustering coefficient and betweenness. It is found that the networks present a significant synchronization different with the equal characteristic path length and clustering coefficient. Simulation results show that neither the characteristic path length nor the clustering coefficient of complex networks can independently demonstrate the synchronization of the complex network. The heterogeneity of the distribution degree essentially suppresses the synchronization of complex networks, while the maximal betweenness is an effective indicator for synchronizability.

Key concepts: Clustering coefficient, Betweenness centrality, Average path length, Synchronization (alternating current), Complex network, Small-world network, Cluster analysis, Computer science

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