Structural efficiency of percolated landscapes in flow networks.
The large-scale structure of complex systems is intimately related to their functionality and evolution. In particular, global transport processes in flow networks rely on the presence of directed pathways from input to output nodes and edges, which organize in macroscopic connected components. However, the precise relation between such structures and functional or evolutionary aspects remains to be understood. Here, we investigate which are the constraints that the global structure of directed networks imposes on transport phenomena. We define quantitatively under minimal assumptions the structural efficiency of networks to determine how robust communication between the core and the peripheral components through interface edges could be. Furthermore, we assess that optimal topologies in terms of access to the core should look like "hairy balls" so to minimize bottleneck effects and the sensitivity to failures. We illustrate our investigation with the analysis of three real networks with very different purposes and shaped by very different dynamics and time-scales-the Internet customer-provider set of relationships, the nervous system of the worm Caenorhabditis elegans, and the metabolism of the bacterium Escherichia coli. Our findings prove that different global connectivity structures result in different levels of structural efficiency. In particular, biological networks seem to be close to the optimal layout.
Serrano
M Angeles
MA
IFISC (CSIC-UIB), Instituto de Física Interdisciplinar y Sistemas Complejos, Campus Universitat Illes Balears, Palma de Mallorca, Spain. marian.serrano@ifisc.uib-csic.es
De Los Rios
Paolo
P
D000818:Animals; D001692:Biological Transport / Q000502:physiology*; D017173:Caenorhabditis elegans / Q000166:cytology / Q000378:metabolism / Q000502:physiology; D002450:Cell Communication / Q000502:physiology; D002451:Cell Compartmentation / Q000502:physiology*; D022082:Cellular Structures / Q000502:physiology*; D004526:Efficiency; D004926:Escherichia coli / Q000166:cytology / Q000378:metabolism / Q000502:physiology; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological; D009415:Nerve Net / Q000378:metabolism / Q000502:physiology; D013312:Stress, Physiological / Q000502:physiology; D013499:Surface Properties