scholarly journals Traffic dynamics of the complex networks with the heterogeneous bandwidth allocation

2013 ◽  
Vol 62 (8) ◽  
pp. 080502
Author(s):  
Yu Hao ◽  
Zhou Yu-Cheng ◽  
Jing Yuan-Wei ◽  
Xu Jia-He ◽  
Zhang Xing-Mei ◽  
...  
Keyword(s):  
Complex Networks ◽  
Bandwidth Allocation ◽  
Traffic Dynamics

Improved efficient routing strategy on two-layer complex networks

2016 ◽  
Vol 27 (04) ◽  
pp. 1650044 ◽  
Author(s):  
Jinlong Ma ◽  
Weizhan Han ◽  
Qing Guo ◽  
Shuai Zhang ◽  
Junfang Wang ◽  
...  
Keyword(s):  
Complex Networks ◽  
Research Topic ◽  
Global Awareness ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Transport Efficiency ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Traffic Performance ◽  
Simulation Results

The traffic dynamics of multi-layer networks has become a hot research topic since many networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the traditional shortest path routing (SPR) protocol is susceptible to congestion on two-layer complex networks. In this paper, we propose an efficient routing strategy named improved global awareness routing (IGAR) strategy which is based on the betweenness centrality of nodes in the two layers. With the proposed strategy, the routing paths can bypass hub nodes of both layers to enhance the transport efficiency. Simulation results show that the IGAR strategy can bring much better traffic capacity than the SPR and the global awareness routing (GAR) strategies. Because of the significantly improved traffic performance, this study is helpful to alleviate congestion of the two-layer complex networks.

Optimal resource allocation strategy for two-layer complex networks

2018 ◽  
Vol 32 (05) ◽  
pp. 1850054 ◽  
Author(s):  
Jinlong Ma ◽  
Lixin Wang ◽  
Sufeng Li ◽  
Congwen Duan ◽  
Yu Liu
Keyword(s):  
Complex Networks ◽  
Service Providers ◽  
Network Capacity ◽  
Capacity Allocation ◽  
Allocation Strategy ◽  
Traffic Dynamics ◽  
Traffic Capacity ◽  
Optimal Value ◽  
Optimal Resource ◽  
Resource Allocation Strategy

We study the traffic dynamics on two-layer complex networks, and focus on its delivery capacity allocation strategy to enhance traffic capacity measured by the critical value [Formula: see text]. With the limited packet-delivering capacity, we propose a delivery capacity allocation strategy which can balance the capacities of non-hub nodes and hub nodes to optimize the data flow. With the optimal value of parameter [Formula: see text], the maximal network capacity is reached because most of the nodes have shared the appropriate delivery capacity by the proposed delivery capacity allocation strategy. Our work will be beneficial to network service providers to design optimal networked traffic dynamics.

scholarly journals Control of epidemic spreading on complex networks by local traffic dynamics

2011 ◽  
Vol 84 (4) ◽  
Author(s):  
Han-Xin Yang ◽  
Wen-Xu Wang ◽  
Ying-Cheng Lai ◽  
Yan-Bo Xie ◽  
Bing-Hong Wang
Keyword(s):  
Complex Networks ◽  
Epidemic Spreading ◽  
Traffic Dynamics

scholarly journals Complex Networks: Traffic Dynamics, Network Performance, and Network Structure

2013 ◽  
Vol 03 (01) ◽  
pp. 187-195 ◽  
Author(s):  
Ziping Hu ◽  
Krishnaiyan Thulasiraman ◽  
Pramode K. Verma
Keyword(s):  
Complex Networks ◽  
Network Structure ◽  
Network Performance ◽  
Traffic Dynamics

Traffic Dynamics on Effective Routing Strategy for Complex Networks

2014 ◽  
Vol 1 ◽  
pp. 539-542
Author(s):  
Takayuki Kimura ◽  
Tohru Ikeguchi
Keyword(s):  
Complex Networks ◽  
Traffic Dynamics ◽  
Routing Strategy

ANALYSIS OF TRAFFIC FLOW ON COMPLEX NETWORKS

2011 ◽  
Vol 25 (10) ◽  
pp. 1419-1428 ◽  
Author(s):  
KUN LI ◽  
XIAOFENG GONG ◽  
SHUGUANG GUAN ◽  
C.-H. LAI
Keyword(s):  
Complex Networks ◽  
Network Capacity ◽  
Traffic Load ◽  
Packet Routing ◽  
Traffic Dynamics ◽  
Scale Free ◽  
Routing Strategy ◽  
Scale Free Networks ◽  
New Strategy ◽  
Mixed Networks

We propose a new routing strategy for controlling packet routing on complex networks. The delivery capability of each node is adopted as a piece of local information to be integrated with the load traffic dynamics to weight the next route. The efficiency of transport on complex network is measured by the network capacity, which is enhanced by distributing the traffic load over the whole network while nodes with high handling ability bear relative heavier traffic burden. By avoiding the packets through hubs and selecting next routes optimally, most travel times become shorter. The simulation results show that the new strategy is not only effective for scale-free networks but also for mixed networks in realistic networks.

Reorganizations of complex networks: Compounding and reducing

2014 ◽  
Vol 25 (05) ◽  
pp. 1440001 ◽  
Author(s):  
Fengjing Shao ◽  
Yi Sui
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Empirical Evidence ◽  
Complex Network ◽  
Traffic Dynamics ◽  
Generalized Framework ◽  
One To One

Real networks interact with each other by different kinds of topological connections, which are usually demonstrated by linking nodes of different networks. Simple connection, such as one-to-one corresponding, random connection and similar connection are adopted for studying the interacted networks. Practical interrelations established between the two networks are ignored. In this study, a generalized framework of multi-subnet composited complex network that allowed us to investigate interrelations among several subnets is developed. Based on that, reorganizations of networks: compounding (compound subnets into a "bigger" one) and reducing (obtain a "smaller" network from a "bigger" one) are proposed. As an empirical evidence, influence of compounding on traffic dynamics is discussed. And the properties of nodes linking two networks are also considered. Onset of compounding between two networks is revealed. Numerical simulations on artificial networks as well as real bus and tube networks of Qingdao in China agree well with our analysis, which show validity of our model.

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