Search

The robustness of realistic infrastructure systems is a significant and long-term research question, which has gotten some constructive outcomes borrowing the framework of complex networks. In this paper, we further explore the method about utilizing optimization algorithms to enhance robustness of interdependent networks. Firstly, we propose a novel particle swarm optimization algorithm with an information feedback mechanism to achieve better performance on complex problems. Secondly, we analyze the solutions from initial loads and types of failed nodes resulted by our algorithm. Interestingly, relative to traditional setup, our algorithm indeed produces a robust resource allocation pattern for interdependent networks, where middle-degree nodes are assigned more tolerance.

With rapid economic and social development, the problem of traffic congestion is getting more and more serious. Accordingly, network traffic models have attracted extensive attention. In this paper, we introduce a shortest-remaining-path-first queuing strategy into a network traffic model on Barabasi–Albert scale-free networks under efficient routing protocol, where one packet’s delivery priority is related to its current distance to the destination. Compared with the traditional first-in-first-out queuing strategy, although the network capacity has no evident changes, some other indexes reflecting transportation efficiency are significantly improved in the congestion state. Extensive simulation results and discussions are carried out to explain the phenomena. Our work may be helpful for the designing of optimal networked-traffic systems.

With the rapid development of economy and the accelerated globalization process, the aviation industry plays more and more critical role in today's world, in both developed and developing countries. As the infrastructure of aviation industry, the airport network is one of the most important indicators of economic growth. In this paper, we investigate the evolution of Chinese airport network (CAN) via complex network theory. It is found that although the topology of CAN remains steady during the past several years, there are many dynamic switchings inside the network, which changes the relative relevance of airports and airlines. Moreover, we investigate the evolution of traffic flow (passengers and cargoes) on CAN. It is found that the traffic keeps growing in an exponential form and it has evident seasonal fluctuations. We also found that cargo traffic and passenger traffic are positively related but the correlations are quite different for different kinds of cities., Comment: 10 pages, 10 figures, Physica A 389 (2010) 3922-3931