Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity

TL;DR

This paper models multilayer networks with finite node storage, revealing how congestion, layer velocity, and capacity influence agent routing, travel times, and network performance, highlighting phenomena like SIF and Braess' paradox.

Contribution

It introduces a dynamic multilayer network model with finite node capacity, analyzing congestion effects and optimal buffer sizes, and uncovers phenomena like SIF and Braess' paradox.

Findings

Optimal buffer size minimizes travel time.

Slower layer velocities can improve overall performance.

Braess' paradox occurs in the multilayer setting.

Abstract

Multilayer networks describe well many real interconnected communication and transportation systems, ranging from computer networks to multimodal mobility infrastructures. Here, we introduce a model in which the nodes have a limited capacity of storing and processing the agents moving over a multilayer network, and their congestions trigger temporary faults which, in turn, dynamically affect the routing of agents seeking for uncongested paths. The study of the network performance under different layer velocities and node maximum capacities, reveals the existence of delicate trade-offs between the number of served agents and their time to travel to destination. We provide analytical estimates of the optimal buffer size at which the travel time is minimum and of its dependence on the velocity and number of links at the different layers. Phenomena reminiscent of the Slower Is Faster (SIF) effect and of the Braess' paradox are observed in our dynamical multilayer set-up.