Complexity metrics for self-monitoring impact sensing networks

Mikhail Prokopenko; Peter Wang; Don Price

doi:10.1109/EH.2005.14

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 proceeding › Conference proceeding contribution › peer-review

10 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Proceedings - 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005
Editors	Jason John
Place of Publication	Los Alamitos, CA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	239-246
Number of pages	8
Volume	2005
ISBN (Print)	0769523994, 9780769523996
DOIs	https://doi.org/10.1109/EH.2005.14
Publication status	Published - 2005
Externally published	Yes
Event	2005 NASA/DoD Conference on Evolvable Hardware, EH-2005 - Washington, DC, United States Duration: 29 Jun 2005 → 1 Jul 2005

Other

Other	2005 NASA/DoD Conference on Evolvable Hardware, EH-2005
Country/Territory	United States
City	Washington, DC
Period	29/06/05 → 1/07/05

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10.1109/EH.2005.14

Cite this

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title = "Complexity metrics for self-monitoring impact sensing networks",

abstract = "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.",

author = "Mikhail Prokopenko and Peter Wang and Don Price",

year = "2005",

doi = "10.1109/EH.2005.14",

language = "English",

isbn = "0769523994",

volume = "2005",

pages = "239--246",

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booktitle = "Proceedings - 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2005 NASA/DoD Conference on Evolvable Hardware, EH-2005 ; Conference date: 29-06-2005 Through 01-07-2005",

}

Prokopenko, M, Wang, P & Price, D 2005, Complexity metrics for self-monitoring impact sensing networks. in J John (ed.), Proceedings - 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005. vol. 2005, 1508506, Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, CA, pp. 239-246, 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005, Washington, DC, United States, 29/06/05. https://doi.org/10.1109/EH.2005.14

Complexity metrics for self-monitoring impact sensing networks. / Prokopenko, Mikhail; Wang, Peter; Price, Don.
Proceedings - 2005 NASA/DoD Conference on Evolvable Hardware, EH-2005. ed. / Jason John. Vol. 2005 Los Alamitos, CA: Institute of Electrical and Electronics Engineers (IEEE), 2005. p. 239-246 1508506.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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Complexity metrics for self-monitoring impact sensing networks

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