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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Minimum energy control for complex networks.

Gustav Lindmark1, Claudio Altafini2

  • 1Division of Automatic Control, Dept. of Electrical Engineering, Linköping University, SE-58183, Linköping, Sweden.

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|February 18, 2018
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Summary
This summary is machine-generated.

Controlling complex networks efficiently requires minimal energy. Energy use is reduced by targeting nodes with a high outdegree-to-indegree ratio, especially for networks with specific eigenvalue properties.

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Area of Science:

  • Network science
  • Control theory
  • Complex systems

Background:

  • Complex networks are ubiquitous in nature and technology.
  • Controlling these networks often requires significant energy.
  • Understanding energy minimization is crucial for efficient network management.

Purpose of the Study:

  • To investigate methods for minimizing control energy in complex networks.
  • To identify key network properties influencing control energy requirements.
  • To develop algorithms for selecting optimal control nodes.

Main Methods:

  • Analysis of network eigenvalues and their relation to control energy.
  • Development of constructive algorithms for minimum control energy driver node selection.
  • Formulation of a heuristic principle based on node degree ratios.

Main Results:

  • Control energy is inversely related to the proximity of network eigenvalues to the imaginary axis.
  • Constructive algorithms were developed for networks with purely imaginary eigenvalues.
  • A general heuristic principle suggests concentrating control on nodes with high outdegree-to-indegree ratios.

Conclusions:

  • Network controllability is optimized by understanding eigenvalue distribution.
  • Specific algorithms and heuristic principles can significantly reduce control energy.
  • Targeting high-ratio nodes offers a general strategy for efficient network control.