An efficient approach of controlling traffic congestion in scale-free networks

We propose and study a model of traffic in communication networks. The underlying network has a structure that is tunable between a scale-free growing network with preferential attachments and a random growing network. To model realistic situations where different nodes in a network may have different capabilities, the message or packet creation and delivering rates at a node are assumed to depend on the degree of the node. Noting that congestions are more likely to take place at the nodes with high degrees in networks with scale-free character, an efficient approach of selectively enhancing the message-processing capability of a small fraction (e.g. 3%) of the nodes is shown to perform just as good as enhancing the capability of all nodes. The interplay between the creation rate and the delivering rate in determining non-congested or congested traffic in a network is studied more numerically and analytically.Comment: 7 pages, 5 figure

Traffic congestion in interconnected complex networks

Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is still relatively unexplored. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected BA scale-free networks. We find that assortative coupling can alleviate traffic congestion more readily than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet AS-level graphs of South Korea and Japan and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnected networks accordingly.Comment: 8 page

Scaling behavior of an artificial traffic model on scale-free networks

In this article, we investigate an artificial traffic model on scale-free networks. Instead of using the routing strategy of the shortest path, a generalized routing algorithm is introduced to improve the transportation throughput, which is measured by the value of the critical point disjoining the free-flow phase and the congested phase. By using the detrended fluctuation analysis, we found that the traffic rate fluctuation near the critical point exhibits the $1/f$-type scaling in the power spectrum. The simulation results agree very well with the empirical data, thus the present model may contribute to the understanding of the underlying mechanism of network traffics.Comment: 6 pages, 5 figure