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Complexity metrics for self-monitoring impact sensing networks

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") graph-theoretic metrics.