Self-organizing hierarchies in sensor and communication networks

Mikhail Prokopenko*, Peter Wang, Philip Valencia, Don Price, Mark Foreman, Anthony Farmer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


We consider a hierarchical multicellular sensing and communication network, embedded in an ageless aerospace vehicle that is expected to detect and react to multiple impacts and damage over a wide range of impact energies. In particular, we investigate self-organization of impact boundaries enclosing critically damaged areas, and impact networks connecting remote cells that have detected noncritical impacts. Each level of the hierarchy is shown to have distinct higher-order emergent properties, desirable in self-monitoring and self-repairing vehicles. In addition, cells and communication messages are shown to need memory (hysteresis) in order to retain desirable emergent behavior within and between various hierarchical levels. Spatiotemporal robustness of self-organizing hierarchies is quantitatively measured with graph-theoretic and information-theoretic techniques, such as the Shannon entropy. This allows us to clearly identify phase transitions separating chaotic dynamics from ordered and robust patterns.

Original languageEnglish
Pages (from-to)407-426
Number of pages20
JournalArtificial Life
Issue number4
Publication statusPublished - Sept 2005
Externally publishedYes


  • Ant colony optimization
  • Impact boundaries
  • Phase transitions
  • Self-organization
  • Sensor networks
  • Stability metrics


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