Improving network traffic capacity by removing links in scale-free networks

2015 ◽  
Author(s):  
Liu Man ◽  
Zhang Shuai ◽  
Zhang Zhifei
Keyword(s):  
Network Traffic ◽  
Scale Free ◽  
Traffic Capacity ◽  
Scale Free Networks

IMPROVED EFFICIENT ROUTING STRATEGY ON SCALE-FREE NETWORKS

2012 ◽  
Vol 23 (02) ◽  
pp. 1250016 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG
Keyword(s):  
Network Traffic ◽  
Traffic Congestion ◽  
Heavy Traffic ◽  
Traffic Load ◽  
Transport Efficiency ◽  
Scale Free ◽  
Network Transport ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Path Cost

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.

A new routing strategy limited by heterogeneous link bandwidth

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.

Enhancing traffic capacity of scale-free networks by link-directed strategy

2016 ◽  
Vol 27 (03) ◽  
pp. 1650028 ◽  
Author(s):  
Jinlong Ma ◽  
Weizhan Han ◽  
Qing Guo ◽  
Shuai Zhang
Keyword(s):  
Communication Networks ◽  
Routing Protocol ◽  
Underlying Structure ◽  
Transport Efficiency ◽  
Scale Free ◽  
Traffic Capacity ◽  
Scale Free Networks ◽  
High Betweenness ◽  
Direction Determining ◽  
High Degree

The transport efficiency of a network is strongly related to the underlying structure. In this paper, we propose an efficient strategy named high-betweenness-first (HBF) for the purpose of improving the traffic handling capacity of scale-free networks by limiting a fraction of undirected links to be unidirectional ones based on the links’ betweenness. Compared with the high-degree-first (HDF) strategy, the traffic capacity can be more significantly enhanced under the proposed link-directed strategy with the shortest path (SP) routing protocol. Simulation results in the Barabási–Albert (BA) model for scale-free networks show that the critical generating rate [Formula: see text] which can evaluate the overall traffic capacity of a network system is larger after applying the HBF strategy, especially with nonrandom direction-determining rules. Because of the strongly improved traffic capacity, this work is helpful to design and optimize modern communication networks such as the software defined network.

Effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks

2017 ◽  
Vol 28 (05) ◽  
pp. 1750066 ◽  
Author(s):  
Zhong-Yuan Jiang ◽  
Jian-Feng Ma
Keyword(s):  
Dynamic Routing ◽  
Scale Free ◽  
Global Dynamic ◽  
Routing Table ◽  
Traffic Capacity ◽  
Scale Free Networks ◽  
Packet Retransmission ◽  
The Cost ◽  
Insight Into ◽  
Real Complex

Existing routing strategies such as the global dynamic routing [X. Ling, M. B. Hu, R. Jiang and Q. S. Wu, Phys. Rev. E 81, 016113 (2010)] can achieve very high traffic capacity at the cost of extremely long packet traveling delay. In many real complex networks, especially for real-time applications such as the instant communication software, extremely long packet traveling time is unacceptable. In this work, we propose to assign a finite Time-to-Live (TTL) parameter for each packet. To guarantee every packet to arrive at its destination within its TTL, we assume that a packet is retransmitted by its source once its TTL expires. We employ source routing mechanisms in the traffic model to avoid the routing-flaps induced by the global dynamic routing. We compose extensive simulations to verify our proposed mechanisms. With small TTL, the effects of packet retransmission on network traffic capacity are obvious, and the phase transition from flow free state to congested state occurs. For the purpose of reducing the computation frequency of the routing table, we employ a computing cycle [Formula: see text] within which the routing table is recomputed once. The simulation results show that the traffic capacity decreases with increasing [Formula: see text]. Our work provides a good insight into the understanding of effects of packet retransmission with finite packet lifetime on traffic capacity in scale-free networks.

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.

Improved efficient queue resource reallocation strategy for traffic dynamics on scale-free networks

2019 ◽  
Vol 30 (08) ◽  
pp. 1950056 ◽  
Author(s):  
Jinlong Ma ◽  
Huiling Wang ◽  
Xiangyang Xu ◽  
Weizhan Han ◽  
Congwen Duan ◽  
...  
Keyword(s):  
Transportation Systems ◽  
Resource Reallocation ◽  
Traffic Dynamics ◽  
Transport Efficiency ◽  
Scale Free ◽  
Traffic Capacity ◽  
Scale Free Networks ◽  
Significant Area ◽  
Simulation Results ◽  
Node Capacity

In recent years, the transportation systems have to face the increasing challenges of congestion and inefficiency, and therefore the research on traffic dynamics of complex networks has become a significant area. When the total node capacity of the network is fixed, a reasonable queue resource reallocation strategy is effective in improving the network traffic capacity. In this paper, a new queue resource allocation method is proposed based on the betweenness centrality and the degree centrality of nodes. With the proposed strategy, the node queue length is allocated accurately to enhance the transport efficiency. Simulation results show that the proposed strategy can effectively improve the traffic capacity of the scale-free networks.

AN EFFICIENT BANDWIDTH ALLOCATION STRATEGY FOR SCALE-FREE NETWORKS

2012 ◽  
Vol 23 (10) ◽  
pp. 1250065 ◽  
Author(s):  
ZHONG-YUAN JIANG ◽  
MAN-GUI LIANG ◽  
SHUAI ZHANG ◽  
SHU-JUAN WANG ◽  
DONG-CHAO GUO
Keyword(s):  
Bandwidth Allocation ◽  
Service Providers ◽  
Network Size ◽  
Urban Transport ◽  
Allocation Strategy ◽  
Transport Networks ◽  
Scale Free ◽  
Traffic Capacity ◽  
Optimal Value ◽  
Scale Free Networks

Traffic capacity is critical for various networks and strongly depends on the distribution of link's bandwidth resources. In this paper, we propose a betweenness-based bandwidth allocation strategy in which the bandwidth of each link lij is allocated proportionally to the product (1 + Bi)α(1 + Bj)α, where α is a tunable parameter, and Bi and Bj are the betweenness of node i and node j, respectively. The optimal value of α is achieved by extensive simulations and slightly increases with the network size. Our new bandwidth allocation strategy achieves the highest traffic capacity when compared with the average bandwidth allocation strategy and the previously proposed degree-based bandwidth allocation strategy. Our work will be beneficial for network service providers to improve the traffic capacity by efficiently allocating or reallocating the overall finite link's bandwidth resources of networks such as the Internet, urban transport networks and airway networks.

Sign in / Sign up

Export Citation Format

Share Document