Quantifying complex network traffic capacity based on communicability sequence entropy

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási–Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

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A new routing strategy limited by heterogeneous link bandwidth

Modern Physics Letters B ◽

10.1142/s0217984918502925 ◽

2018 ◽

Vol 32 (24) ◽

pp. 1850292

Author(s):

Xin Wang ◽

Feng Chen ◽

Tao Zhang ◽

Ning Qin ◽

Zhong-Yuan Jiang

Keyword(s):

Communication Networks ◽

Network Traffic ◽

Network Routing ◽

Network Systems ◽

Shortest Path Routing ◽

Scale Free ◽

Traffic Capacity ◽

Network Diameter ◽

Potential Applications ◽

New Perspective

Traffic capacity of a network is very vital to a variety of complex networks, such as communication networks and road networks, in which the bandwidth of every link is limited or finite. In this work, inspired by the deployment process of nodes and links in real networks, we assume the bandwidth of every link is composed of a constant part and a degree-related one that can be updated iteratively with the network hardware update. We propose a link bandwidth-based routing mechanism to enhance the network traffic capacity. Extensive simulations in both scale-free networks and random networks are done to confirm the effectiveness of our proposed method. Comparing results with the shortest path routing and a weighted routing, our method achieves better network traffic capacity among all used routing strategies without obvious extra cost including the network diameter, average path length and average packet traveling time. Our work studies network routing from a very new perspective and might have potential applications in real network systems such as the communication networks.

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Complex network comparison based on communicability sequence entropy

Physical Review E ◽

10.1103/physreve.98.012319 ◽

2018 ◽

Vol 98 (1) ◽

Cited By ~ 5

Author(s):

Dan Chen ◽

Dan-Dan Shi ◽

Mi Qin ◽

Si-Meng Xu ◽

Gui-Jun Pan

Keyword(s):

Complex Network ◽

Sequence Entropy ◽

Network Comparison

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Research on Key Technologies of Network Traffic Identification in Complex Network Environment Based on Deep Learning

Proceedings of the 2020 International Conference on Computers, Information Processing and Advanced Education ◽

10.1145/3419635.3419679 ◽

2020 ◽

Author(s):

Guanglu Wei

Keyword(s):

Deep Learning ◽

Complex Network ◽

Network Traffic ◽

Network Environment ◽

Traffic Identification ◽

Key Technologies

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The Traffic Capacity Variation of Urban Road Network due to the Policy of Unblocking Community

Complexity ◽

10.1155/2021/9292389 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Xin Feng ◽

Yue Zhang ◽

Shuo Qian ◽

Liming Sun

Keyword(s):

Complex Network ◽

Traffic Congestion ◽

Gated Communities ◽

Urban Traffic ◽

Assessment Model ◽

Capacity Assessment ◽

Global Dynamics ◽

Urban Road ◽

Model Based ◽

Traffic Capacity

At present, urban traffic congestion is a common problem of urban development in China. Therefore, China’s government issued the policy of opening the gated communities in 2016, hoping to alleviate traffic pressure to some extent. But, at present, the quantitative empirical research on the effect of the policy implementation is less and more idealistic. In order to complete the leap from research on local isolated traffic capacity of static gated communities to research on global coupling traffic capacity of dynamic multilayer network and, to a certain extent, reflect the innovation of the research model and method, we make a quantitative analysis of the effect of the policy more consistent with the actual situation, which provides a quantitative management basis for the implementation of the policy. Based on literature review, this paper carried out two stages of research. Stage one consists of constructing traffic capacity assessment model—Road Capacity Assessment (RCA) model based on BPR (Bureau of Public Roads) impedance function from a simple local static perspective. Considering the factors such as delay of signalized intersection and travel time, through modeling analysis and empirical test, it is found that about 12% of local traffic capacity can be improved after open community. Stage two consists of constructing a global capacity model based on multilayer complex network coupling from the perspective of complex global dynamics. Considering the various network nodes of pedestrians, nonmotor vehicles, and other factors, we construct a multilayer complex network and dynamic superposition coupling. The empirical data show that the overall traffic capacity of the open community is improved by at least 11.3%. Finally, it can be concluded that a significant increase in the global traffic capacity of complex urban road networks means that the losses caused by traffic congestion will be reduced. In some first-tier cities, the direct monthly income of the open-gated community is as high as 230 million yuan, not to mention its overall economic, social, and environmental benefits.

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Enhancing traffic capacity for multilayer networks by link rewiring

International Journal of Modern Physics B ◽

10.1142/s0217979221502544 ◽

2021 ◽

pp. 2150254

Author(s):

Min Li ◽

Jinlong Ma ◽

Junfeng Zhang

Keyword(s):

Network Structure ◽

Network Traffic ◽

High Speed ◽

Layer Structure ◽

Average Length ◽

Packet Transmission ◽

Multilayer Networks ◽

Traffic Dynamics ◽

Low Speed ◽

Traffic Capacity

The traffic dynamics of complex networks is closely related to network structure. By changing network structure, the traffic dynamics behavior can be optimized. Faced with the network congestion problem, we focus on the relationship between network traffic capacity and its structure. The multilayer networks are studied, which are composed of high-speed and low-speed layers. A link rewiring strategy is proposed to change the low-speed layer structure and improve the network traffic capacity. Compared with the random link rewiring strategy, the purposeful link rewiring strategy can improve network traffic capacity. A large number of simulations are carried out under the effective traffic-flow assignment strategy to prove the effectiveness of the link rewiring strategy. This strategy improves packet transmission efficiency of low-speed layer, and reduces the average length of effective path, which indicates that adjustment of low-speed layer structure can improve traffic capacity of multilayer networks.

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ENHANCING TRAFFIC CAPACITY OF TWO-LAYER COMPLEX NETWORKS

International Journal of Modern Physics C ◽

10.1142/s0129183113500514 ◽

2013 ◽

Vol 24 (08) ◽

pp. 1350051 ◽

Cited By ~ 18

Author(s):

ZHONG-YUAN JIANG ◽

MAN-GUI LIANG ◽

SHUAI ZHANG ◽

WEIXING ZHOU ◽

HUIQIN JIN

Keyword(s):

Complex Systems ◽

Network Model ◽

Network Traffic ◽

Physical Layer ◽

Traffic Load ◽

Traffic Dynamics ◽

Shortest Path Routing ◽

Routing Strategy ◽

Traffic Capacity ◽

Real Complex

As two-layer or multi-layer network model can more accurately reveal many real structures of complex systems such as peer-to-peer (P2P) networks on IP networks, to better understand the traffic dynamics and improve the network traffic capacity, we propose to efficiently construct the structure of upper logical layer network which can be possibly implemented. From the beginning, we assume that the logical layer network has the same structure as the lower physical layer network, and then we use link-removal strategy in which a fraction of links with maximal product (ki* kj) are removed from the logical layer, where ki and kj are the degrees of node i and node j, respectively. Traffic load is strongly redistributed from center nodes to noncenter nodes. The traffic capacity of whole complex system is enhanced several times at the expense of a little average path lengthening. In two-layer network model, the physical layer network structure is unchanged and the shortest path routing strategy is used. The structure of upper layer network can been constructed freely under our own methods. This mechanism can be employed in many real complex systems to improve the network traffic capacity.

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