scholarly journals Enhancing traffic capacity of multilayer networks with two logical layers by link deletion

2021 ◽  
Author(s):  
Jinlong Ma ◽  
Zhichao Sun ◽  
Yongqiang Zhang
Keyword(s):  
Multilayer Networks ◽  
Traffic Capacity

An efficient improved routing strategy for multilayer networks

2020 ◽  
pp. 2150078
Author(s):  
Jinlong Ma ◽  
Min Li ◽  
Yaming Li ◽  
Xiangyang Xu ◽  
Weizhan Han ◽  
...  
Keyword(s):  
Multilayer Structure ◽  
High Speed ◽  
Multilayer Networks ◽  
Traffic Dynamics ◽  
The Core ◽  
Transmission Process ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Average Transmission ◽  
Simulation Results

Traffic dynamics of multilayer networks draws continuous attention from different communities since many systems are actually proved to have a multilayer structure. Since the core nodes of network are prone to congested, an effective routing strategy is of great significance to alleviate the congestion of the multilayer networks. In this paper, we propose an efficient improved routing strategy, with which the core nodes that can reasonably avoid congestion at the high-speed layer in the transmission process of packets, and can also make the most of the traffic resources of the low-speed layer nodes to optimize the traffic capacity of multilayer networks. The simulation results show that the proposed routing strategy can not only improve the network traffic capacity, but also shorten the average path length and average transmission time.

Enhancing traffic capacity for multilayer networks by link rewiring

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.

An efficient resource allocation strategy for multilayer networks

2021 ◽  
Vol 35 (05) ◽  
pp. 2150073
Author(s):  
Yongqiang Zhang ◽  
Yaming Li ◽  
Min Li ◽  
Jinlong Ma ◽  
Zhaohui Qi
Keyword(s):  
Resource Allocation ◽  
Utilization Efficiency ◽  
Network Congestion ◽  
Allocation Strategy ◽  
Multilayer Networks ◽  
Network Resources ◽  
Simulation Experiments ◽  
Traffic Capacity ◽  
Efficient Resource ◽  
Resource Allocation Strategy

The resource allocation strategy plays an important role in the improvement of network traffic capacity. In order to solve the problem of network congestion, an efficient resource allocation strategy is proposed for multilayer networks to optimize the utilization efficiency of network resources. With the proposed strategy, the network resources are allocated to nodes more reasonable and the network congestions are evidently reduced. Simulation experiments show that the proposed resource allocation strategy can greatly improve the traffic capacity of the multilayer networks compared with the average resource allocation strategy. The proposed strategy can give full play to the traffic resources of multilayer networks, which has guiding significance for optimizing the existing networks and building new networks.

Traffic dynamics on multilayer networks with two logical layers

2021 ◽  
pp. 2150109
Author(s):  
Jinlong Ma ◽  
Zhichao Sun ◽  
Yongqiang Zhang ◽  
Xiangyang Xu ◽  
Ruimei Zhao ◽  
...  
Keyword(s):  
Network Model ◽  
Random Network ◽  
Physical Layer ◽  
Random Networks ◽  
Scale Free Network ◽  
Multilayer Networks ◽  
Traffic Dynamics ◽  
Scale Free ◽  
Traffic Capacity ◽  
Free Network

In order to study traffic dynamics on multilayer networks, it is of great significance to build a network model which can more exactly reflect the actual network layered structure characteristics. In this paper, a three-layer network model in which two logical layers are mapped on one physical layer is established, and the traffic capacities of three kinds of multilayer networks with different combinations of logical layers are compared. Simulation results show that when the physical layer is the same random network, the network whose logical layers are two random networks has the optimal traffic capacity, the network with one random network and one scale-free network in the logical layers has the better traffic capacity than the network whose logical layers are two scale-free networks.

Research on Traffic Capacity of Eight-Lane Freeways under Lane Management

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Pei Liu ◽  
Xiucheng Guo ◽  
Yang Bai ◽  
Yi Li ◽  
Ruiying Lu
Keyword(s):  
Traffic Capacity

Diffusion

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
Random Walks ◽  
Spectral Properties ◽  
Diffusion Constant ◽  
Network Structures ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Lévy Walk ◽  
Number Of Layers ◽  
Levy Walk ◽  
Speed Up

This chapter addresses diffusion, random walks and congestion in multilayer networks. Here it is revealed that diffusion on a multilayer network can be significantly speed up with respect to diffusion taking place on its single layers taken in isolation, and that sometimes it is possible also to observe super-diffusion. Diffusion is here characterized on multilayer network structures by studying the spectral properties of the supra-Laplacian and the dependence on the diffusion constant among different layers. Random walks and its variations including the Lévy Walk are shown to reflect the improved navigability of multilayer networks with more layers. These results are here compared with the results of traffic on multilayer networks that, on the contrary, point out that increasing the number of layers could be detrimental and could lead to congestion.

Centrality Measures

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
State Of The Art ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Multilayer Networks ◽  
Comprehensive Description ◽  
Multilayer Network ◽  
Suitable Definition ◽  
Katz Centrality ◽  
Pagerank Centrality

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.

Networks

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Complex Systems ◽  
Complex Networks ◽  
Phase Diagrams ◽  
Community Detection ◽  
Network Science ◽  
Small World ◽  
Small World Networks ◽  
Multilayer Networks ◽  
Basic Vocabulary

Understanding the interactions between the components of a system is key to understanding it. In complex systems, interactions are usually not uniform, not isotropic and not homogeneous: each interaction can be specific between elements.Networks are a tool for keeping track of who is interacting with whom, at what strength, when, and in what way. Networks are essential for understanding of the co-evolution and phase diagrams of complex systems. Here we provide a self-contained introduction to the field of network science. We introduce ways of representing and handle networks mathematically and introduce the basic vocabulary and definitions. The notions of random- and complex networks are reviewed as well as the notions of small world networks, simple preferentially grown networks, community detection, and generalized multilayer networks.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

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