Self-adjusting routing schemes for time-varying traffic in scale-free networks

Effective traffic-flow assignment strategy on multilayer networks

An efficient flow assignment strategy is of great importance to alleviate traffic congestion on multilayer networks. In this work, by considering the roles of nodes' local structures on the microlevel, and the different transporting speeds of layers in the macrolevel, an effective traffic-flow assignment strategy on multilayer networks is proposed. Both numerical and semianalytical results indicate that our proposed flow assignment strategy can reasonably redistribute the traffic flow of the low-speed layer to the high-speed layer. In particular, preferentially transporting the packets through small-degree nodes on the high-speed layer can enhance the traffic capacity of multilayer networks. We also find that the traffic capacity of multilayer networks can be improved by increasing the network size and the average degree of the high-speed layer. For a given multilayer network, there is a combination of optimal macrolevel parameter and optimal microlevel parameter with which the traffic capacity can be maximized. It is verified that real-world network topology does not invalidate the results. The semianalytical predictions agree with the numerical simulations.

Traffic-driven epidemic outbreak on complex networks: how long does it take?

Recent studies have suggested the necessity to incorporate traffic dynamics into the process of epidemic spreading on complex networks, as the former provides support for the latter in many real-world situations. While there are results on the asymptotic scope of the spreading dynamics, the issue of how fast an epidemic outbreak can occur remains outstanding. We observe numerically that the density of the infected nodes exhibits an exponential increase with time initially, rendering definable a characteristic time for the outbreak. We then derive a formula for scale-free networks, which relates this time to parameters characterizing the traffic dynamics and the network structure such as packet-generation rate and betweenness distribution. The validity of the formula is tested numerically. Our study indicates that increasing the average degree and/or inducing traffic congestion can slow down the spreading process significantly.

Epidemic spreading with information-driven vaccination

Epidemic spreading has been well studied in the past decade, where the main concentration is focused on the influence of network topology but little attention is paid to the individual's crisis awareness. We here study how the crisis awareness, i.e., personal self-protection, influences the epidemic spreading by presenting a susceptible-infected-recovered model with information-driven vaccination. We introduce two parameters to quantitatively characterize the crisis awareness. One is the information creation rate λ and the other is the information sensitivity η. We find that the epidemic spreading can be significantly suppressed in both the homogeneous and heterogeneous networks when both λ and η are relatively large. More interesting is that the needed vaccine will be significantly reduced when the information is well spread, which is a good news for the poor countries and regions with limited resources.

Control of epidemic spreading on complex networks by local traffic dynamics

Despite extensive work on traffic dynamics and epidemic spreading on complex networks, the interplay between these two types of dynamical processes has not received adequate attention. We study the effect of local-routing-based traffic dynamics on epidemic spreading. For the case of unbounded node-delivery capacity, where the traffic is free of congestion, we obtain analytic and numerical results indicating that the epidemic threshold can be maximized by an optimal routing protocol. This means that epidemic spreading can be effectively controlled by local traffic dynamics. For the case of bounded delivery capacity, numerical results and qualitative arguments suggest that traffic congestion can suppress epidemic spreading. Our results provide quantitative insight into the nontrivial role of traffic dynamics associated with a local-routing scheme in the epidemic spreading.

Efficient routing strategies in scale-free networks with limited bandwidth

We study the traffic dynamics in complex networks where each link is assigned a limited and identical bandwidth. Although the first-in-first-out (FIFO) queuing rule is widely applied in the routing protocol of information packets, here we argue that if we drop this rule, the overall throughput of the network can be remarkably enhanced. We propose some efficient routing strategies that do not strictly obey the FIFO rule. Compared to the routine shortest-path strategy, throughput for both Barabási-Albert (BA) networks and the Internet can be improved by a factor of more than five. We calculate the theoretical limitation of the throughput. In BA networks, our proposed strategy can achieve 88% of the theoretical optimum, yet for the Internet, it is about 12%, implying that we still have a huge space to further improve the routing strategy for the Internet. Finally, we discuss possibly promising ways to design more efficient routing strategies for the Internet.

Transportation dynamics on networks of mobile agents

Most existing works on transportation dynamics focus on networks of a fixed structure, but networks whose nodes are mobile have become widespread, such as cell-phone networks. We introduce a model to explore the basic physics of transportation on mobile networks. Of particular interest is the dependence of the throughput on the speed of agent movement and the communication range. Our computations reveal a hierarchical dependence for the former, while an algebraic power law is found between the throughput and the communication range with the exponent determined by the speed. We develop a physical theory based on the Fokker-Planck equation to explain these phenomena. Our findings provide insights into complex transportation dynamics arising commonly in natural and engineering systems.

Effective strategy of adding nodes and links for maximizing the traffic capacity of scale-free network

In this paper, we propose an efficient strategy to enhance traffic capacity via the process of nodes and links increment. We show that by adding shortcut links to the existing networks, packets are avoided flowing through hub nodes. We investigate the performances of our proposed strategy under the shortest path routing strategy and the local routing strategy. Our obtained results show that using the proposed strategy, the traffic capacity can be effectively enhanced under the shortest path routing strategy. Under the local routing strategy, the obtained results show that the proposed strategy is efficient only when packets are more likely to be forwarded to low-degree nodes in their routing paths. Compared with other strategies, the obtained results indicate that our proposed strategy of adding nodes and links is the most effective in enhancing the traffic capacity, i.e., the traffic capacity can be maximally enhanced with the least number of additional nodes and links.

Coverage-maximization in networks under resource constraints

Efficient coverage algorithms are essential for information search or dispersal in all kinds of networks. We define an extended coverage problem which accounts for constrained resources of consumed bandwidth B and time T . Our solution to the network challenge is here studied for regular grids only. Using methods from statistical mechanics, we develop a coverage algorithm with proliferating message packets and temporally modulated proliferation rate. The algorithm performs as efficiently as a single random walker but O(B(d-2)/d) times faster, resulting in significant service speed-up on a regular grid of dimension d . The algorithm is numerically compared to a class of generalized proliferating random walk strategies and on regular grids shown to perform best in terms of the product metric of speed and efficiency.