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Interplay between signaling network design and swarm dynamics

Published online by Cambridge University Press:  23 May 2016

ANDRÉ SEKUNDA ,
MOHAMMAD KOMAREJI  and
ROLAND BOUFFANAIS
ANDRÉ SEKUNDA
Affiliation:
Aalborg University, Fredrik Bajers Vej 5, 9220 Aalborg Ø, Denmark (e-mail: [email protected])
MOHAMMAD KOMAREJI
Affiliation:
SUTD–MIT International Design Centre, Singapore University of Technology and Design, 8 Somapah Road, 487372, Singapore (e-mail: [email protected])
ROLAND BOUFFANAIS
Affiliation:
Singapore University of Technology and Design, 8 Somapah Road, 487372, Singapore (e-mail: [email protected])
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Abstract

Distributed information transfer is of paramount importance to the effectiveness of dynamic collective behaviors, especially when a swarm is confronted with complex environmental circumstances. Recently, the signaling network of interaction underlying such effective information transfers has been revealed in the particular case of bird flocks governed by a topological interaction. Such biological systems are known to be evolutionary optimized, but are also constrained by the very nature of the signaling mechanisms—owing to intrinsic limitations in sensory modalities—enabling communication among individuals. Here, we propose that artificial swarm design can be tackled from the angle of signaling network design. To this aim, we use different network models to investigate the impact of some network structural properties on the effectiveness of a specific emergent swarming behavior, namely global consensus. Two new network models are introduced, which together with the well-known Watts–Strogatz model form the basis for an analysis of the relationship between clustering, shortest path and speed to consensus. A network-theoretic approach combined with spectral graph theory tools are used to propose some signaling network design principles. Eventually, one key design principle—a concomitant reduction in clustering and connecting path—is successfully tested on simulations of swarms of self-propelled particles.

Keywords

interaction networkswarming systemstemporal networks
Type
Research Article
Information
Network Science , Volume 4 , Issue 2 , June 2016 , pp. 244 - 265
Copyright
Copyright © Cambridge University Press 2016 

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