Effective traffic-flow assignment strategy on multilayer networks.

Area of Science:

• Network Science
• Complex Systems
• Traffic Engineering

Background:

• Traffic congestion is a major challenge in multilayer networks.
• Understanding microlevel node structures and macrolevel layer speeds is crucial for efficient flow assignment.

Purpose of the Study:

• To develop an effective traffic-flow assignment strategy for multilayer networks.
• To enhance the traffic capacity and alleviate congestion in these networks.

Main Methods:

• Proposed a novel flow assignment strategy considering both local node structures and layer transport speeds.
• Utilized numerical simulations and semianalytical methods for validation.
• Analyzed the impact of network size, average degree, and optimal parameter combinations.

Main Results:

• The strategy effectively redistributes traffic from low-speed to high-speed layers.
• Preferential routing through small-degree nodes on high-speed layers enhances traffic capacity.
• Increasing network size and high-speed layer average degree improves capacity.
• Optimal microlevel and macrolevel parameters maximize traffic capacity.

Conclusions:

• The proposed strategy offers a viable solution for managing traffic flow in multilayer networks.
• Findings are robust and applicable to real-world network topologies.
• Semianalytical predictions align with numerical simulation results, validating the approach.