Effect of shortest path multiplicity on congestion of multiplex networks

Solé-Ribalta, Albert; Arenas, Àlex; Gómez, Sergio

doi:10.1088/1367-2630/ab023e

Cited by 25 publications

(11 citation statements)

References 37 publications

(64 reference statements)

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“…Transport in a multilayer network, where layers correspond to transport modes, is often studied using diffusion or spreading processes [1,[16][17][18]. Many of these works use shortest-path minimization [14,[19][20][21] as the main method to extract the passengers' trajectories. However, this can be a restrictive choice: on one side, this assumes that different layers share the same cost function to be minimized; on the other side, shortest-path minimization is not sensitive to traffic congestion and thus, may not be realistic in certain scenarios.…”

Section: Introductionmentioning

confidence: 99%

Optimal Transport in Multilayer Networks for Traffic Flow Optimization

2021

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Modeling traffic distribution and extracting optimal flows in multilayer networks is of the utmost importance to design efficient, multi-modal network infrastructures. Recent results based on optimal transport theory provide powerful and computationally efficient methods to address this problem, but they are mainly focused on modeling single-layer networks. Here, we adapt these results to study how optimal flows distribute on multilayer networks. We propose a model where optimal flows on different layers contribute differently to the total cost to be minimized. This is done by means of a parameter that varies with layers, which allows to flexibly tune the sensitivity to the traffic congestion of the various layers. As an application, we consider transportation networks, where each layer is associated to a different transportation system, and show how the traffic distribution varies as we tune this parameter across layers. We show an example of this result on the real, 2-layer network of the city of Bordeaux with a bus and tram, where we find that in certain regimes, the presence of the tram network significantly unburdens the traffic on the road network. Our model paves the way for further analysis of optimal flows and navigability strategies in real, multilayer networks.

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Section: Introductionmentioning

confidence: 99%

Optimal Transport in Multilayer Networks for Traffic Flow Optimization

2021

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“…When we investigate the dynamics of multiplex network, the number of shortest paths must be considered together with the intralayer paths and interlayer paths through a certain node. e critical packet injection rate of the multiplex network is as follows [19,25,27]:…”

Section: Methodsmentioning

confidence: 99%

“…However, in a multiplex network, there are two distinct kinds of shortest paths: paths that only use a single layer and paths that use more than one layer. e dynamic process in multiplex networks is becoming a hot spot of current research [17][18][19][20][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Enhance the Transfer Capacity of Multiplex Networks

2021

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Most complex real systems are found to have multiple layers of connectivity and required to be modelled as multiplex networks. One of the extremely critical problems is to reduce the congestion and enhance the transfer capacity, especially in real communication networks with a big data environment. A novel and effective strategy to improve traffic and control congestion is proposed by adding edges according to their weights which are defined by the topology structural properties. Furthermore, which layer is more effective when our strategy is applied is discussed based on its topology structure. Adding edges between nodes whose product of multiplex network betweenness is the highest is confirmed to be more effective, particularly in the layer with stronger community structure. Simulation experiments on both computer-generated and real-world networks demonstrate that our strategy can enhance the transfer capacity of multiplex networks significantly, which is in good agreement with our analysis.

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“…Transport in a multilayer network, where layers correspond to transport modes, has often been studied using diffusion or spreading processes [1,[16][17][18]. Many of these works use shortest-path minimization [14,[19][20][21] as the main method to extract the passengers' trajectories. However, this can be a restrictive choice: on one side, this assumes that different layers share the same cost function to be minimized; on the other side, shortest-path minimization is not sensitive to traffic congestion and thus may not be realistic in certain scenarios.…”

Section: Introductionmentioning

confidence: 99%

Optimal transport in multilayer networks for traffic flow optimization

Ibrahim,

Lonardi,

De Bacco

2021

Preprint

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Modeling traffic distribution and extracting optimal flows in multilayer networks is of utmost importance to design efficient multi-modal network infrastructures. Recent results based on optimal transport theory provide powerful and computationally efficient methods to address this problem, but they are mainly focused on modeling single-layer networks. Here we adapt these results to study how optimal flows distribute on multilayer networks. We propose a model where optimal flows on different layers contribute differently to the total cost to be minimized. This is done by means of a parameter that varies with layers, which allows to flexibly tune the sensitivity to traffic congestion of the various layers. As an application, we consider transportation networks, where each layer is associated to a different transportation system and show how the traffic distribution varies as we tune this parameter across layers. We show an example of this result on the real 2-layer network of the city of Bordeaux with bus and tram, where we find that in certain regimes the presence of the tram network significantly unburdens the traffic on the road network. Our model paves the way to further analysis of optimal flows and navigability strategies in real multilayer networks.

show abstract

Effect of shortest path multiplicity on congestion of multiplex networks

Cited by 25 publications

References 37 publications

Optimal Transport in Multilayer Networks for Traffic Flow Optimization

Optimal Transport in Multilayer Networks for Traffic Flow Optimization

Enhance the Transfer Capacity of Multiplex Networks

Optimal transport in multilayer networks for traffic flow optimization

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