Complexity metrics for self-monitoring impact sensing networks

Mikhail Prokopenko*, Peter Wang, Don Price

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

10 Citations (Scopus)


In this paper we describe novel metrics measuring complexity in self-organising networks. The metrics are investigated within the context of decentralised inspections, developed and implemented as part of the joint CSIRO-NASA Ageless Aerospace Vehicle (AAV) research project. The AAV Concept Demonstrator is a hardware multi-cellular sensing and communication network which is expected to detect and react to multiple impacts, without any centralised controllers. We present an extension of an Ant Colony Optimisation algorithm, using an Adaptive Dead Reckoning Scheme and producing robust and reconfigurable minimum spanning trees connecting autonomous AAV cells. We then introduce a new metric detecting emergence through irregularities in the multi-agent communications, and contrast it with conventional macro-level ("global-view") graphtheoretic metrics.

Original languageEnglish
Title of host publicationProceedings - 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005
EditorsJason John
Place of PublicationLos Alamitos, CA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Print)0769523994, 9780769523996
Publication statusPublished - 2005
Externally publishedYes
Event2005 NASA/DoD Conference on Evolvable Hardware, EH-2005 - Washington, DC, United States
Duration: 29 Jun 20051 Jul 2005


Other2005 NASA/DoD Conference on Evolvable Hardware, EH-2005
Country/TerritoryUnited States
CityWashington, DC


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