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Effective Augmentation of Complex Networks.

Jinjian Wang1, Xinghuo Yu1, Lewi Stone2

  • 1School of Engineering, RMIT University, Melbourne, 3000, Australia.

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We developed an "effective augmentation" algorithm to efficiently grow networks by adding nodes while preserving structural controllability. This method optimizes network expansion for various applications without needing extra driver-nodes.

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Area of Science:

  • Networks science
  • Systems theory
  • Control theory

Background:

  • Networks are crucial in modern society, from power grids to social media.
  • Optimizing network growth while maintaining control is a significant challenge.

Purpose of the Study:

  • To develop a method for augmenting networks by adding nodes without compromising structural controllability.
  • To conserve the number of driver-nodes during network expansion.

Main Methods:

  • Introduced an "effective augmentation" algorithm.
  • Leveraged intrinsic network topology clusters for efficient node addition.
  • Algorithm allows rapid augmentation of many nodes in a single time-step.

Main Results:

  • The "effective augmentation" algorithm successfully optimizes network growth.
  • Demonstrated efficacy across diverse model and real-world networks.
  • Preserves structural controllability during network expansion.

Conclusions:

  • The "effective augmentation" method provides an efficient way to grow networks.
  • Applicable to biological, social, power, and technological networks.
  • Offers significant practical and economic value for network management.