On Consensus of Star-Composed Networks with an Application of Laplacian Spectrum

Da Huang, Haijun Jiang, Zhiyong Yu, Qiongxiang Huang and Xing Chen

Discrete Dynamics in Nature and Society, 2017, vol. 2017, 1-13

Abstract:

In this paper, we mainly study the performance of star-composed networks which can achieve consensus. Specifically, we investigate the convergence speed and robustness of the consensus of the networks, which can be measured by the smallest nonzero eigenvalue of the Laplacian matrix and the norm of the graph, respectively. In particular, we introduce the notion of the corona of two graphs to construct star-composed networks and apply the Laplacian spectrum to discuss the convergence speed and robustness for the communication network. Finally, the performances of the star-composed networks have been compared, and we find that the network in which the centers construct a balanced complete bipartite graph has the most advantages of performance. Our research would provide a new insight into the combination between the field of consensus study and the theory of graph spectra.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:4619514

DOI: 10.1155/2017/4619514

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