### Abstract

To design complex networks to minimize traffic congestion, it is necessary to understand how traffic flow depends on network structure. We study data packet flow on complex networks, where the packet delivery capacity of each node is not fixed. The optimal configuration of capacities to minimize traffic congestion is derived and the critical packet generating rate is determined, below which the network is at a free flow state but above which congestion occurs. Our analysis reveals a direct relation between network topology and traffic flow. Optimal network structure, free of traffic congestion, should have two features: uniform distribution of load over all nodes and small network diameter. This finding is confirmed by numerical simulations. Our analysis also makes it possible to theoretically compare the congestion conditions for different types of complex networks. In particular, we find that network with low critical generating rate is more susceptible to congestion. The comparison has been made on the following complex-network topologies: random, scale-free, and regular.

Original language | English (US) |
---|---|

Article number | 043103 |

Journal | Chaos |

Volume | 17 |

Issue number | 4 |

DOIs | |

State | Published - 2007 |

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### ASJC Scopus subject areas

- Applied Mathematics
- Physics and Astronomy(all)
- Statistical and Nonlinear Physics
- Mathematical Physics

### Cite this

*Chaos*,

*17*(4), [043103]. https://doi.org/10.1063/1.2790367

**Optimal structure of complex networks for minimizing traffic congestion.** / Zhao, Liang; Cupertino, Thiago Henrique; Park, Kwangho; Lai, Ying-Cheng; Jin, Xiaogang.

Research output: Contribution to journal › Article

*Chaos*, vol. 17, no. 4, 043103. https://doi.org/10.1063/1.2790367

}

TY - JOUR

T1 - Optimal structure of complex networks for minimizing traffic congestion

AU - Zhao, Liang

AU - Cupertino, Thiago Henrique

AU - Park, Kwangho

AU - Lai, Ying-Cheng

AU - Jin, Xiaogang

PY - 2007

Y1 - 2007

N2 - To design complex networks to minimize traffic congestion, it is necessary to understand how traffic flow depends on network structure. We study data packet flow on complex networks, where the packet delivery capacity of each node is not fixed. The optimal configuration of capacities to minimize traffic congestion is derived and the critical packet generating rate is determined, below which the network is at a free flow state but above which congestion occurs. Our analysis reveals a direct relation between network topology and traffic flow. Optimal network structure, free of traffic congestion, should have two features: uniform distribution of load over all nodes and small network diameter. This finding is confirmed by numerical simulations. Our analysis also makes it possible to theoretically compare the congestion conditions for different types of complex networks. In particular, we find that network with low critical generating rate is more susceptible to congestion. The comparison has been made on the following complex-network topologies: random, scale-free, and regular.

AB - To design complex networks to minimize traffic congestion, it is necessary to understand how traffic flow depends on network structure. We study data packet flow on complex networks, where the packet delivery capacity of each node is not fixed. The optimal configuration of capacities to minimize traffic congestion is derived and the critical packet generating rate is determined, below which the network is at a free flow state but above which congestion occurs. Our analysis reveals a direct relation between network topology and traffic flow. Optimal network structure, free of traffic congestion, should have two features: uniform distribution of load over all nodes and small network diameter. This finding is confirmed by numerical simulations. Our analysis also makes it possible to theoretically compare the congestion conditions for different types of complex networks. In particular, we find that network with low critical generating rate is more susceptible to congestion. The comparison has been made on the following complex-network topologies: random, scale-free, and regular.

UR - http://www.scopus.com/inward/record.url?scp=37649014217&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=37649014217&partnerID=8YFLogxK

U2 - 10.1063/1.2790367

DO - 10.1063/1.2790367

M3 - Article

C2 - 18163767

AN - SCOPUS:37649014217

VL - 17

JO - Chaos (Woodbury, N.Y.)

JF - Chaos (Woodbury, N.Y.)

SN - 1054-1500

IS - 4

M1 - 043103

ER -