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Frailty Assessment in an Aging Mouse Model
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Fragility Limits Performance in Complex Networks.

Fabio Pasqualetti1, Shiyu Zhao2, Chiara Favaretto3,4

  • 1University of California at Riverside, Department of Mechanical Engineering, Riverside, 92521, CA, USA. fabiopas@engr.ucr.edu.

Scientific Reports
|February 6, 2020
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Summary
This summary is machine-generated.

Large networks exhibit a performance-robustness tradeoff, meaning they can be either robust or efficient, but not both. This fundamental limitation impacts natural evolution and human design across diverse network types.

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Area of Science:

  • Network science
  • Systems biology
  • Complexity science

Background:

  • Numerous studies indicate large networks (biological, social, technological) are fragile.
  • Existing theories fail to explain the lack of optimization against fragility in natural evolution and human design.

Purpose of the Study:

  • To provide analytical and numerical evidence for a tradeoff between robustness and performance in networks with linear dynamics.
  • To explain why simultaneous optimization of network robustness and performance is not achieved.

Main Methods:

  • Analytical modeling of networks with linear dynamics.
  • Numerical simulations across various network models.
  • Analysis of simplified models for ecological, neuronal, and traffic networks.

Main Results:

  • A fundamental tradeoff exists between network robustness and performance.
  • Networks can be optimized for either robustness (stability) or performance (efficiency), but not both.
  • This tradeoff is observed across diverse network types, including ecological, neuronal, and traffic systems.

Conclusions:

  • The observed performance-robustness tradeoff is a key factor limiting network optimization.
  • This limitation is inherent in network design and evolution, explaining observed fragility.
  • Findings have broad implications for understanding and designing complex systems.