Narrow Results

The transport efficiency is one of the critical parameters to evaluate the performance of a network. In this paper, we propose an improved efficient (IE) strategy to enhance the network transport efficiency of complex networks by adding a fraction of links to an existing network based on the node’s local degree centrality and the shortest path length. Simulation results show that the proposed strategy can bring better traffic capacity and shorter average shortest path length than the low-degree-first (LDF) strategy under the shortest path routing protocol. It is found that the proposed strategy is beneficial to the improvement of overall traffic handling and delivering ability of the network. This study can alleviate the congestion in networks, and is helpful to design and optimize realistic networks.

In this paper, we investigate the random walks on metro systems in 28 cities from worldwide via the Laplacian spectrum to realize the trapping process on real systems. The average trapping time is a primary description to response the trapping process. Firstly, we calculate the mean trapping time to each target station and to each entire system, respectively. Moreover, we also compare the average trapping time with the strength (the weighted degree) and average shortest path length for each station, separately. It is noted that the average trapping time has a close inverse relation with the station’s strength but rough positive correlation with the average shortest path length. And we also catch the information that the mean trapping time to each metro system approximately positively correlates with the system’s size. Finally, the trapping process on weighted and unweighted metro systems is compared to each other for better understanding the influence of weights on trapping process on metro networks. Numerical results show that the weights have no significant impact on the trapping performance on metro networks.