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Related Experiment Video

Updated: Jun 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Generalized priority-queue network dynamics: impact of team and hierarchy.

Won-kuk Cho¹, Byungjoon Min, K-I Goh

¹Department of Physics, Korea University, Seoul 136-713, Korea.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|September 28, 2010

Summary

This summary is machine-generated.

We investigated how team dynamics and hierarchy influence waiting times in priority-queue networks. Our findings show power-law waiting-time distributions, with exponents varying by team size and hierarchical position.

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Last Updated: Jun 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Operations Research
Network Science
Queueing Theory

Background:

Priority-queue networks are fundamental in various systems, from computing to logistics.
Understanding waiting-time dynamics is crucial for optimizing system performance and resource allocation.
Existing models often simplify the complex interactions within these networks.

Purpose of the Study:

To analyze the impact of team-based execution and hierarchical decision-making on waiting-time distributions in priority-queue networks.
To develop generalized models that capture these complex interaction rules.
To identify key factors driving the observed waiting-time dynamics.

Main Methods:

Introduction of generalized priority-queue network models.
Incorporation of team-execution interaction rules.
Incorporation of hierarchy-based decision-making interaction rules.
Numerical analysis of waiting-time distributions.

Main Results:

Waiting-time distributions exhibit power-law behavior for long waiting times in both team and hierarchy models.
The exponents of the power laws are dependent on team size and hierarchical node position.
Pairwise queue interactions are suggested as a significant dynamic consequence.
Reciprocity of influence is identified as a relevant factor in network dynamics.

Conclusions:

Team size and hierarchy significantly alter waiting-time dynamics in priority-queue networks.
Power-law behavior in waiting times is a robust feature, influenced by network structure.
Pairwise interactions and reciprocal influence are critical elements for understanding these complex systems.