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Optimization of synchronizability in complex spatial networks

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  • Al Khafaf, Nameer
  • Jalili, Mahdi

Abstract

Many real-world phenomena can be modelled as spatial networks where nodes have distinct geographical location. Examples include power grids, transportation networks and the Internet. This paper focuses on optimizing the synchronizability of spatial networks. We consider the eigenratio of the Laplacian Matrix of the connection graph as a metric measuring the synchronizability of the network and develop an efficient rewiring mechanism to optimize the topology of the network for synchronizability, i.e., minimizing the eigenratio. The Euclidean distance between two connected nodes is considered as their connection weights, and the sum of all connection weights is defined as the network cost. The proposed optimization algorithm constructs spatial networks with a certain number of nodes and a predefined network cost. We also study the topological properties of the optimized networks. This algorithm can be used to construct spatial networks with optimal synchronization properties.

Suggested Citation

  • Al Khafaf, Nameer & Jalili, Mahdi, 2019. "Optimization of synchronizability in complex spatial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 46-55.
    • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:46-55
    DOI: 10.1016/j.physa.2018.09.030
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    References listed on IDEAS

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    1. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    2. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    3. Jon M. Kleinberg, 2000. "Navigation in a small world," Nature, Nature, vol. 406(6798), pages 845-845, August.
    4. Saniee Monfared, Momhammad Ali & Jalili, Mahdi & Alipour, Zohreh, 2014. "Topology and vulnerability of the Iranian power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 24-33.
    5. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
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    Cited by:

    1. Yan, Jiaye & Zhou, Jiaying & Wu, Zhaoyan, 2019. "Structure identification of unknown complex-variable dynamical networks with complex coupling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 256-265.

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