| CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
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Self-Organized Optimization of Transport on Complex Networks |
| Rui-Wu Niu, Gui-Jun Pan** |
Faculty of Physics and Electronic Technology, Hubei University, Wuhan 430062
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| Cite this article: |
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Rui-Wu Niu, Gui-Jun Pan 2016 Chin. Phys. Lett. 33 068901 |
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Abstract We propose a self-organized optimization mechanism to improve the transport capacity of complex gradient networks. We find that, regardless of network topology, the congestion pressure can be strongly reduced by the self-organized optimization mechanism. Furthermore, the random scale-free topology is more efficient to reduce congestion compared with the random Poisson topology under the optimization mechanism. The reason is that the optimization mechanism introduces the correlations between the gradient field and the local topology of the substrate network. Due to the correlations, the cutoff degree of the gradient network is strongly reduced and the number of the nodes exerting their maximal transport capacity consumedly increases. Our work presents evidence supporting the idea that scale-free networks can efficiently improve their transport capacity by self-organized mechanism under gradient-driven transport mode.
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Received: 14 November 2015
Published: 30 June 2016
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| PACS: |
89.75.Hc
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(Networks and genealogical trees)
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05.40.Fb
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(Random walks and Levy flights)
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89.75.Fb
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(Structures and organization in complex systems)
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89.75.Da
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(Systems obeying scaling laws)
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