Efficient packet navigation method on scale-free networks with finite and diversiform node delivery capacity

2016 ◽  
Vol 27 (09) ◽  
pp. 1650098
Author(s):  
Xuan He ◽  
Kai Niu ◽  
Zhiqiang He ◽  
Jiaru Lin ◽  
Hui Zhang ◽  
...  

Routing strategy is essential for high transport efficiency on realistic networked complex systems. Beginning from the consideration of finite and diversiform node delivery capacity distributions, a general node capacity allocation mechanism with a tunable parameter [Formula: see text] is presented. A node capacity, based routing strategy is proposed to improve the network traffic capacity. Compared with the traditional shortest path routing (SPR) and the efficient routing (ER) methods, it suggests that routing strategy should be chosen heuristically according to the limited capacity resource distribution, instead of using one certain method for all cases. With proper range of parameter [Formula: see text], the new routing strategy achieves the highest traffic capacity and other preferable measure metrics including network diameter, average path length, efficient betweenness, average packet travel time and average traffic load. The theoretical analysis for traffic capacity has a good correspondence to the simulation results. This work studies routing mechanisms from a very practical perspective, and helps network researchers to understand the traffic dynamics on complex networks comprehensively.

2014 ◽  
Vol 25 (09) ◽  
pp. 1450044 ◽  
Author(s):  
Zhong-Yuan Jiang

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.


2012 ◽  
Vol 26 (29) ◽  
pp. 1250195 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG ◽  
JIAN-LING HUANG ◽  
QIAN LI

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.


2015 ◽  
Vol 26 (10) ◽  
pp. 1550118 ◽  
Author(s):  
Xuan He ◽  
Kai Niu ◽  
Zhiqiang He ◽  
Jiaru Lin ◽  
Zhong-Yuan Jiang

Provided that node delivery capacity may be not uniformly distributed in many realistic networks, we present a node delivery capacity distribution in which each node capacity is composed of uniform fraction and degree related proportion. Based on the node delivery capacity distribution, we construct a novel routing mechanism called efficient weighted routing (EWR) strategy to enhance network traffic capacity and transportation efficiency. Compared with the shortest path routing and the efficient routing strategies, the EWR achieves the highest traffic capacity. After investigating average path length, network diameter, maximum efficient betweenness, average efficient betweenness, average travel time and average traffic load under extensive simulations, it indicates that the EWR appears to be a very effective routing method. The idea of this routing mechanism gives us a good insight into network science research. The practical use of this work is prospective in some real complex systems such as the Internet.


2015 ◽  
Vol 29 (17) ◽  
pp. 1550085 ◽  
Author(s):  
Hui Zhang ◽  
Zhong-Yuan Jiang ◽  
Xuan He ◽  
Shuai Zhang

Since the delivery capacity of each node is neither uniform nor strictly proportional to the degree in many real networked systems such as the Internet, we consider the node capacity is composed of a small uniform fraction and a large degree dependent proportion. By comparing the optimal routing strategy [B. Danila, Y. Yu, J. A. Marsh and K. E. Bassler, Phys. Rev. E 74 (2006) 046106; B. Danila, Y. Yu, J. A. Marsh and K. E. Bassler, Chaos 17 (2007) 026102] with the shortest path routing (SPR), the results show that the OR appears to be not efficient enough to enhance network traffic capacity. Then the efficient betweenness defined as the average betweenness for per delivery capacity is employed, and a so-called highly-efficient routing (HER) strategy is proposed. By iteratively minimizing the maximum efficient betweenness of any node in the network, the highest traffic capacity is achieved at the cost of a little average path lengthening. This work is very useful for network service providers to optimize the weight of each link incrementally to improve whole network transport ability.


2012 ◽  
Vol 23 (02) ◽  
pp. 1250016 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG

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.


2018 ◽  
Vol 32 (24) ◽  
pp. 1850292
Author(s):  
Xin Wang ◽  
Feng Chen ◽  
Tao Zhang ◽  
Ning Qin ◽  
Zhong-Yuan Jiang

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.


2018 ◽  
Vol 32 (13) ◽  
pp. 1850155 ◽  
Author(s):  
Jinlong Ma ◽  
Huiling Wang ◽  
Zhuxi Zhang ◽  
Yi Zhang ◽  
Congwen Duan ◽  
...  

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.


2013 ◽  
Vol 24 (08) ◽  
pp. 1350051 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG ◽  
SHUAI ZHANG ◽  
WEIXING ZHOU ◽  
HUIQIN JIN

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.


2017 ◽  
Vol 28 (07) ◽  
pp. 1750087 ◽  
Author(s):  
Yibo Yang ◽  
Honglin Zhao ◽  
Jinlong Ma ◽  
Zhaohui Qi ◽  
Yongbin Zhao

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.


2016 ◽  
Vol 27 (04) ◽  
pp. 1650044 ◽  
Author(s):  
Jinlong Ma ◽  
Weizhan Han ◽  
Qing Guo ◽  
Shuai Zhang ◽  
Junfang Wang ◽  
...  

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.


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