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Strategy for community control of complex networks

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  • Piao, Xiufeng
  • Lv, Tianyang
  • Zhang, Xizhe
  • Ma, Hui

Abstract

The latest researches have explored the topic of complex network control based on the linear system control theory. These researches aim to control all nodes of a network. However, in many cases it is sufficient to control just a part of nodes. Because a community usually plays an independent role in a real complex system, the paper discusses a strategy to control target communities of a complex network. First, the paper shows that the process of controlling target communities will be influenced by their connections with the remainder of the network. Therefore, it is necessary to block the control signals transmitting through these interconnections. Second, the paper proposes a new kind of control nodes that selectively block signal transmissions, termed immune nodes. The immune nodes work along with the driver nodes to facilitate the control of target communities, even if the entire topology of a network is absent. Third, we propose a method to reduce the total number of driver nodes and control nodes by deliberately arranging the matching sequence of nodes. The experiments are carried out on a series of model networks and 11 real networks. The experimental results show that the absolute control cost of controlling communities is less than that of controlling the entire network, when the average degree of the network is low, but the ratio of immune nodes and driver nodes to all nodes increases.

Suggested Citation

  • Piao, Xiufeng & Lv, Tianyang & Zhang, Xizhe & Ma, Hui, 2015. "Strategy for community control of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 98-108.
    • Handle: RePEc:eee:phsmap:v:421:y:2015:i:c:p:98-108
    DOI: 10.1016/j.physa.2014.10.081
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    References listed on IDEAS

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    1. Dirk Helbing, 2013. "Globally networked risks and how to respond," Nature, Nature, vol. 497(7447), pages 51-59, May.
    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. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    4. Kenneth Button & Roger R. Stough, 2000. "Air Transport Networks," Books, Edward Elgar Publishing, number 2148.
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    Cited by:

    1. Zhang, Xizhe & Zhu, Yuyan & Zhao, Yongkang, 2021. "Altering control modes of complex networks by reversing edges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    2. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.

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