Rules for biologically inspired adaptive network design.
Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield re...
Main Authors: | , , , , , , , , |
---|---|
Format: | Journal article |
Language: | English |
Published: |
2010
|
_version_ | 1797050479245524992 |
---|---|
author | Tero, A Takagi, S Saigusa, T Ito, K Bebber, D Fricker, M Yumiki, K Kobayashi, R Nakagaki, T |
author_facet | Tero, A Takagi, S Saigusa, T Ito, K Bebber, D Fricker, M Yumiki, K Kobayashi, R Nakagaki, T |
author_sort | Tero, A |
collection | OXFORD |
description | Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks--in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains. |
first_indexed | 2024-03-06T18:05:46Z |
format | Journal article |
id | oxford-uuid:01616eb5-3b21-4848-8b63-f909f34a83cc |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-06T18:05:46Z |
publishDate | 2010 |
record_format | dspace |
spelling | oxford-uuid:01616eb5-3b21-4848-8b63-f909f34a83cc2022-03-26T08:34:38ZRules for biologically inspired adaptive network design.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:01616eb5-3b21-4848-8b63-f909f34a83ccEnglishSymplectic Elements at Oxford2010Tero, ATakagi, SSaigusa, TIto, KBebber, DFricker, MYumiki, KKobayashi, RNakagaki, TTransport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks--in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains. |
spellingShingle | Tero, A Takagi, S Saigusa, T Ito, K Bebber, D Fricker, M Yumiki, K Kobayashi, R Nakagaki, T Rules for biologically inspired adaptive network design. |
title | Rules for biologically inspired adaptive network design. |
title_full | Rules for biologically inspired adaptive network design. |
title_fullStr | Rules for biologically inspired adaptive network design. |
title_full_unstemmed | Rules for biologically inspired adaptive network design. |
title_short | Rules for biologically inspired adaptive network design. |
title_sort | rules for biologically inspired adaptive network design |
work_keys_str_mv | AT teroa rulesforbiologicallyinspiredadaptivenetworkdesign AT takagis rulesforbiologicallyinspiredadaptivenetworkdesign AT saigusat rulesforbiologicallyinspiredadaptivenetworkdesign AT itok rulesforbiologicallyinspiredadaptivenetworkdesign AT bebberd rulesforbiologicallyinspiredadaptivenetworkdesign AT frickerm rulesforbiologicallyinspiredadaptivenetworkdesign AT yumikik rulesforbiologicallyinspiredadaptivenetworkdesign AT kobayashir rulesforbiologicallyinspiredadaptivenetworkdesign AT nakagakit rulesforbiologicallyinspiredadaptivenetworkdesign |