TRAFFIC CONGESTION ANALYSIS IN COMPLEX NETWORKS BASED ON VARIOUS ROUTING STRATEGIES

2007 ◽  
Vol 21 (15) ◽  
pp. 929-939 ◽  
Author(s):  
XUAN GUO ◽  
HONGTAO LU
Keyword(s):  
Complex Networks ◽  
Traffic Congestion ◽  
Small World ◽  
Modern Society ◽  
Information Communication ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Deterministic Routing ◽  
Routing Strategy ◽  
Network Topologies

Networks, acting as infrastructure for information communication, play an important role in modern society, therefore, the elements affecting the efficiency of network traffic are worthy of deep research. In this paper, we investigate numerically the problem of traffic congestion in complex networks through the use of various routing strategies. Three types of complex networks structures, namely Poisson random networks, small-world networks and scale-free networks, are considered. Three different routing strategies are used on networks: deterministic routing strategy, preferential routing strategy and shortest path routing strategy. We evaluate the efficiency of different routing strategies on different network topologies and show how the network structures and routing strategies influence the traffic congestion status.

AN EFFICIENT WEIGHTED ROUTING STRATEGY FOR SCALE-FREE NETWORKS

2012 ◽  
Vol 26 (29) ◽  
pp. 1250195 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG ◽  
JIAN-LING HUANG ◽  
QIAN LI
Keyword(s):  
Traffic Congestion ◽  
Heavy Traffic ◽  
Traffic Load ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Edge Betweenness ◽  
Real Complex ◽  
Link Congestion

Considering the link congestion based traffic model, which can more accurately model the traffic diffusing process of many real complex systems such as the Internet, we propose an efficient weighted routing strategy in which each link's weight is assigned with the edge betweenness of the original un-weighted network with a tunable parameter α. As the links with the highest edge betweenness are susceptible to traffic congestion, our routing strategy efficiently redistribute the heavy traffic load from central links to noncentral links. The highest traffic capacity under this new routing strategy is achieved when compared with the shortest path routing strategy and the efficient routing strategy. Moreover, the average path length of our routing strategy is much smaller than that of the efficient routing strategy. Therefore, our weighted routing strategy is preferable to other routing strategies and can be easily implemented through software method.

An efficient routing strategy for traffic dynamics on two-layer complex networks

2018 ◽  
Vol 32 (13) ◽  
pp. 1850155 ◽  
Author(s):  
Jinlong Ma ◽  
Huiling Wang ◽  
Zhuxi Zhang ◽  
Yi Zhang ◽  
Congwen Duan ◽  
...  
Keyword(s):  
Complex Networks ◽  
Traffic Congestion ◽  
Physical Layer ◽  
Traffic Load ◽  
Global Awareness ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Routing Strategy ◽  
Optimal Paths ◽  
Traffic Capacity

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

scholarly journals Quantitative Controllability Index of Complex Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Lifu Wang ◽  
Yali Zhang ◽  
Jingxiao Han ◽  
Zhi Kong
Keyword(s):  
Complex Networks ◽  
Condition Number ◽  
Random Network ◽  
Small World ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
The Relationship ◽  
Controllability Index

In this paper, the controllability issue of complex network is discussed. A new quantitative index using knowledge of control centrality and condition number is constructed to measure the controllability of given networks. For complex networks with different controllable subspace dimensions, their controllability is mainly determined by the control centrality factor. For the complex networks that have the equal controllable subspace dimension, their different controllability is mostly determined by the condition number of subnetworks’ controllability matrix. Then the effect of this index is analyzed based on simulations on various types of network topologies, such as ER random network, WS small-world network, and BA scale-free network. The results show that the presented index could reflect the holistic controllability of complex networks. Such an endeavour could help us better understand the relationship between controllability and network topology.

An optimal routing strategy on scale-free networks

2017 ◽  
Vol 28 (07) ◽  
pp. 1750087 ◽  
Author(s):  
Yibo Yang ◽  
Honglin Zhao ◽  
Jinlong Ma ◽  
Zhaohui Qi ◽  
Yongbin Zhao
Keyword(s):  
Traffic Congestion ◽  
Transportation Systems ◽  
Optimal Routing ◽  
Shortest Path Routing ◽  
Transport Efficiency ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Traffic Performance ◽  
Scale Free Networks

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

CONGESTION AND EFFICIENCY IN COMPLEX TRAFFIC NETWORKS

2013 ◽  
Vol 24 (10) ◽  
pp. 1350072 ◽  
Author(s):  
JIAN-FENG ZHENG ◽  
ZHI-HONG ZHU ◽  
HAO-MING DU ◽  
ZI-YOU GAO
Keyword(s):  
Complex Networks ◽  
Small World ◽  
Traffic Networks ◽  
Flow State ◽  
Traffic Demand ◽  
Scale Free ◽  
Link Cost ◽  
Network Topologies ◽  
The Impact ◽  
The Relationship

This paper investigates the degree of congestion and efficiency in complex traffic networks, by introducing congestion effects, which can be described by flow-based link cost functions. Different network topologies including random networks, small-world networks and scale-free networks are explored. The impact of different distributions of capacity and origin-destination traffic demand on the degree of congestion and efficiency in complex networks is mainly studied. A phase transition from free flow state to traffic jams can be uncovered. The relationship between congestion and efficiency in complex networks is also discussed.

scholarly journals Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiuwen Fu ◽  
Yongsheng Yang ◽  
Haiqing Yao
Keyword(s):  
Random Network ◽  
Small World ◽  
Coupled Map Lattice ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

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.

COMPLEX NETWORKS: TOPOLOGY, DYNAMICS AND SYNCHRONIZATION

2002 ◽  
Vol 12 (05) ◽  
pp. 885-916 ◽  
Author(s):  
XIAO FAN WANG
Keyword(s):  
Complex Networks ◽  
Network Models ◽  
Small World ◽  
Dynamical Networks ◽  
Scale Free ◽  
Epidemic Dynamics ◽  
The Past ◽  
The Relationship

Dramatic advances in the field of complex networks have been witnessed in the past few years. This paper reviews some important results in this direction of rapidly evolving research, with emphasis on the relationship between the dynamics and the topology of complex networks. Basic quantities and typical examples of various complex networks are described; and main network models are introduced, including regular, random, small-world and scale-free models. The robustness of connectivity and the epidemic dynamics in complex networks are also evaluated. To that end, synchronization in various dynamical networks are discussed according to their regular, small-world and scale-free connections.

An incremental optimal routing strategy for scale-free networks

2014 ◽  
Vol 25 (09) ◽  
pp. 1450044 ◽  
Author(s):  
Zhong-Yuan Jiang
Keyword(s):  
Traffic Load ◽  
Traffic Model ◽  
Optimal Routing ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Real Complex ◽  
Link Congestion

The link congestion based traffic model can more accurately reveal the traffic dynamics of many real complex networks such as the Internet, and heuristically optimizing each link's weight for the shortest path routing strategy can strongly improve the traffic capacity of network. In this work, we propose an optimal routing strategy in which the weight of each link is regulated incrementally to enhance the network traffic capacity by minimizing the maximum link betweenness of any link in the network. We also estimate more suitable value of the tunable parameter β for the efficient routing strategy under the link congestion based traffic model. The traffic load of network can be significantly balanced at the expense of increasing a bit average path length or average traffic load.

Propagation and stability in software: A complex network perspective

2015 ◽  
Vol 26 (05) ◽  
pp. 1550052 ◽  
Author(s):  
Lei Wang ◽  
Ping Wang
Keyword(s):  
Software Engineering ◽  
Complex Networks ◽  
Large Scale ◽  
Structural Difference ◽  
Small World ◽  
Change Propagation ◽  
Small World Networks ◽  
Typical Structure ◽  
Scale Free ◽  
Scale Free Networks

In this paper, we attempt to understand the propagation and stability feature of large-scale complex software from the perspective of complex networks. Specifically, we introduced the concept of "propagation scope" to investigate the problem of change propagation in complex software. Although many complex software networks exhibit clear "small-world" and "scale-free" features, we found that the propagation scope of complex software networks is much lower than that of small-world networks and scale-free networks. Furthermore, because the design of complex software always obeys the principles of software engineering, we introduced the concept of "edge instability" to quantify the structural difference among complex software networks, small-world networks and scale-free networks. We discovered that the edge instability distribution of complex software networks is different from that of small-world networks and scale-free networks. We also found a typical structure that contributes to the edge instability distribution of complex software networks. Finally, we uncovered the correlation between propagation scope and edge instability in complex networks by eliminating the edges with different instability ranges.

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