Congestion-gradient driven transport on complex networks
Bogdan Danila, Yong Yu, Samuel Earl, John A. Marsh, Zoltan Toroczkai, Kevin E. Bassler
Abstract
We present a study of transport on complex networks with routing based on local information. Particles hop from one node of the network to another according to a set of routing rules with different degrees of congestion awareness, ranging from random diffusion to rigid congestion-gradient driven flow. Each node can be either source or destination for particles and all nodes have the same routing capacity, which are features of ad-hoc wireless networks. It is shown that the transport capacity increases when a small amount of congestion awareness is present in the routing rules, and that it then decreases as the routing rules become too rigid when the flow becomes strictly congestion-gradient driven. Therefore, an optimum value of the congestion awareness exists in the routing rules. It is also shown that, in the limit of a large number of nodes, networks using routing based on local information jam at any nonzero load. Finally, we study the correlation between congestion at node level and a betweenness centrality measure.
Create a lesson
Related papers
Long-time Dynamics of Many-body Open Quantum Systems using Quantum Generating Functions
Katha Ganguly, Dario Poletti, Bijay Kumar Agarwalla
Localization Delocalization Transition in Diffusion with Adaptive Resetting
Tommer D. Keidar, Shlomi Reuveni
Quenched activity induces nonuniversal scaling in nonreciprocal XY Models and surfaces
Sudip Mukherjee, Abhik Basu
Brownian yet non-Gaussian diffusion through equilibrium nonlinear friction
Jakob Mihatsch, Andreas M. Menzel
When dissipative steady states admit thermodynamic occupation laws
Tetsu Ichitsubo
Fluctuation--response relations from an emergent Z2 symmetry in the rotating stochastic Landau model
Dhruv Kush, Nicki Mullins, Mauricio Hippert et al.