arXiv subjects

Ming Tang

Publications and source records attributed to Ming Tang.

At least 253 records · Page 14Linked to original sources

arXiv2014

Suppressed epidemics in multi-relational networks

A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w1 and w0 occur with probabilities p and 1-p, respectively. The fraction of infected nodes rho(p) shows a non-monotonic behavior, with rho drops with p for small p and increases for large p. For small to moderate w1/w0 ratios, rho(p) exhibits a minimum that signifies an optimal suppression. For large w1/w0 ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range p_L =< p =< p_R, and an active phase with mixed infected and healthy nodes for p < p_L and p>p_R. A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w0 links and within clusters formed by nodes carrying the w1 links is presented. The absorbing state at large w1/w0 ratios results when the clusters are big enough to disrupt the spread via w0 links and yet small enough to avoid an epidemic within the clusters. A theory that uses the possible local environments of a node as variables is formulated. The theory gives results in good agreement with simulation results, thereby showing the necessity of including longer spatial correlations.

physics.soc-ph↗

arXiv2014

Message spreading in networks with stickiness and persistence: Large clustering does not always facilitate large-scale diffusion

Recent empirical studies have confirmed the key roles of complex contagion mechanisms such as memory, social reinforcement, and decay effects in information diffusion and behaviour spreading. Inspired by this fact, we here propose a new agent--based model to capture the whole picture of the joint action of the three mechanisms in information spreading, by quantifying the complex contagion mechanisms as stickiness and persistence, and carry out extensive simulations of the model on various networks. By numerical simulations as well as theoretical analysis, we find that the stickiness of the message determines the critical dynamics of message diffusion on tree-like networks, whereas the persistence plays a decisive role on dense regular lattices. In either network, the greater persistence can effectively make the message more invasive. Of particular interest is that our research results renew our previous knowledge that messages can spread broader in networks with large clustering, which turns out to be only true when they can inform a non-zero fraction of the population in the limit of large system size.

physics.soc-ph↗

arXiv2014

Epidemic spreading on complex networks with general degree and weight distributions

The spread of disease on complex networks has attracted widely attention in the physics community. Recent works have demonstrated that heterogeneous degree and weight distributions have a significant influence on the epidemic dynamics. In this study, a novel edge-weight based compartmental approach is developed to estimate the epidemic threshold and epidemic size (final infected density) on networks with general degree and weight distributions, and a remarkable agreement with numerics is obtained. Even in complex network with the strong heterogeneous degree and weight distributions, this approach is worked. We then propose an edge-weight based removal strategy with different biases, and find that such a strategy can effectively control the spread of epidemic when the highly weighted edges are preferentially removed, especially when the weight distribution of a network is extremely heterogenous. The theoretical results from the suggested method can accurately predict the above removal effectiveness.

physics.soc-ph↗

arXiv2014

Asymmetrically interacting spreading dynamics on complex layered networks

The spread of disease through a physical-contact network and the spread of information about the disease on a communication network are two intimately related dynamical processes. We investigate the asymmetrical interplay between the two types of spreading dynamics, each occurring on its own layer, by focusing on the two fundamental quantities underlying any spreading process: epidemic threshold and the final infection ratio. We find that an epidemic outbreak on the contact layer can induce an outbreak on the communication layer, and information spreading can effectively raise the epidemic threshold. When structural correlation exists between the two layers, the information threshold remains unchanged but the epidemic threshold can be enhanced, making the contact layer more resilient to epidemic outbreak. We develop a physical theory to understand the intricate interplay between the two types of spreading dynamics.

physics.soc-ph↗

arXiv2014

Efficient allocation of heterogeneous response times in information spreading process

Recently, the impacts of spatiotemporal heterogeneities of human activities on spreading dynamics have attracted extensive attention. In this paper, to study heterogeneous response times on information spreading, we focus on the susceptible-infected spreading dynamics with adjustable power-law response time distribution based on uncorrelated scale-free networks. We find that the stronger the heterogeneity of response times is, the faster the information spreading is in the early and middle stages. Following a given heterogeneity, the procedure of reducing the correlation between the response times and degrees of individuals can also accelerate the spreading dynamics in the early and middle stages. However, the dynamics in the late stage is slightly more complicated, and there is an optimal value of the full prevalence time changing with the heterogeneity of response times and the response time-degree correlation, respectively. The optimal phenomena results from the efficient allocation of heterogeneous response times.

physics.soc-ph↗

arXiv2013

Signal transmission in a Y-shaped one-way chain

It has been found that noise plays a key role to improve signal transmission in a one-way chain of bistable systems [Zhang et al., Phys. Rev. E 58, 2952 (1998)]. We here show that the signal transmission can be sharply improved without the aid of noise, if the one-way chain with a single source node is changed with two source nodes becoming a Y-shaped one-way chain. We further reveal that the enhanced signal transmission in the Y-shaped one-way chain is regulated by coupling strength, and that it is robust to noise perturbation and input signal irregularity. We finally analyze the mechanism of the enhanced signal transmission by the Y-shaped structure.

physics.soc-ph↗

arXiv2013

Influence of Reciprocal links in Social Networks

In this Letter, we empirically study the influence of reciprocal links, in order to understand its role in affecting the structure and function of directed social networks. Experimental results on two representative datesets, Sina Weibo and Douban, demonstrate that the reciprocal links indeed play a more important role than non-reciprocal ones in both spreading information and maintaining the network robustness. In particular, the information spreading process can be significantly enhanced by considering the reciprocal effect. In addition, reciprocal links are largely responsible for the connectivity and efficiency of directed networks. This work may shed some light on the in-depth understanding and application of the reciprocal effect in directed online social networks.

physics.soc-ph↗

arXiv2012

Optimal forwarding ratio on dynamical networks with heterogeneous mobility

As the discovery of non-Poissonian statistics of human mobility trajectories, more attention has been paid to understanding the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate the forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in the case of random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged in small and large high-speed value. It is interesting to find that the slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from local structural heterogeneity of low-speed agents.

physics.soc-ph↗

arXiv2012

Emergence of scale-free close-knit friendship structure in online social networks

Despite the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter -- the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree.

physics.soc-ph↗

arXiv2012

Effects of Weak Ties on Epidemic Predictability in Community Networks

Weak ties play a significant role in the structures and the dynamics of community networks. Based on the susceptible-infected model in contact process, we study numerically how weak ties influence the predictability of epidemic dynamics. We first investigate the effects of different kinds of weak ties on the variabilities of both the arrival time and the prevalence of disease, and find that the bridgeness with small degree can enhance the predictability of epidemic spreading. Once weak ties are settled, compared with the variability of arrival time, the variability of prevalence displays a diametrically opposed changing trend with both the distance of the initial seed to the bridgeness and the degree of the initial seed. More specifically, the further distance and the larger degree of the initial seed can induce the better predictability of arrival time and the worse predictability of prevalence. Moreover, we discuss the effects of weak tie number on the epidemic variability. As community strength becomes very strong, which is caused by the decrease of weak tie number, the epidemic variability will change dramatically. Compared with the case of hub seed and random seed, the bridgenss seed can result in the worst predictability of arrival time and the best predictability of prevalence. These results show that the variability of arrival time always marks a complete reversal trend of that of prevalence, which implies it is impossible to predict epidemic spreading in the early stage of outbreaks accurately.

physics.soc-ph↗

arXiv2012

Efficient community-based control strategies in adaptive networks

Most researches on adaptive networks mainly concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structures in transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing modularity $Q$, we investigate the evolution of community structures during the transient process, and find that very strong community structures are induced by rewiring mechanism in the early stage of epidemic spreading, which remarkably delays the outbreaks of epidemic. Then we study the effects of control strategies started from different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not "the earlier, the better" for the implementing of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of strong community structure. For immunization strategy, immunizing the S nodes on SI links and immunizing S nodes randomly have similar control effects. Yet for quarantine strategy, quarantining the I nodes on SI links can yield far better effects than quarantining I nodes randomly. More significantly, community-based quarantine strategy plays more efficient performance than community-based immunization strategy. This study may shed new lights on the forecast and the prevention of epidemic among human population.

physics.soc-ph↗

arXiv2012

Variability of Contact Process in Complex Networks

We study numerically how the structures of distinct networks influence the epidemic dynamics in contact process. We first find that the variability difference between homogeneous and heterogeneous networks is very narrow, although the heterogeneous structures can induce the lighter prevalence. Contrary to non-community networks, strong community structures can cause the secondary outbreak of prevalence and two peaks of variability appeared. Especially in the local community, the extraordinarily large variability in early stage of the outbreak makes the prediction of epidemic spreading hard. Importantly, the bridgeness plays a significant role in the predictability, meaning the further distance of the initial seed to the bridgeness, the less accurate the predictability is. Also, we investigate the effect of different disease reaction mechanisms on variability, and find that the different reaction mechanisms will result in the distinct variabilities at the end of epidemic spreading.

physics.soc-ph↗

arXiv2012

Epidemic Variability in Hierarchical Geographical Networks with Human Activity Patterns

Recently, some studies have revealed that non-Poissonian statistics of human behaviors stem from the hierarchical geographical network structure. On this view, we focus on epidemic spreading in the hierarchical geographical networks, and study how two distinct contact patterns (i. e., homogeneous time delay (HOTD) and heterogeneous time delay (HETD) associated with geographical distance) influence the spreading speed and the variability of outbreaks. We find that, compared with HOTD and null model, correlations between time delay and network hierarchy in HETD remarkably slow down epidemic spreading, and result in a upward cascading multi-modal phenomenon. Proportionately, the variability of outbreaks in HETD has the lower value, but several comparable peaks for a long time, which makes the long-term prediction of epidemic spreading hard. When a seed (i. e., the initial infected node) is from the high layers of networks, epidemic spreading is remarkably promoted. Interestingly, distinct trends of variabilities in two contact patterns emerge: high-layer seeds in HOTD result in the lower variabilities, the case of HETD is opposite. More importantly, the variabilities of high-layer seeds in HETD are much greater than that in HOTD, which implies the unpredictability of epidemic spreading in hierarchical geographical networks.

physics.soc-ph↗

arXiv2012

Slow dynamics of Zero Range Process in the Framework of Traps Model

The relaxation dynamics of zero range process (ZRP) has always been an interesting problem. In this study, we set up the relationship between ZRP and traps model, and investigate the slow dynamics of ZRP in the framework of traps model. Through statistical quantities such as the average rest time, the particle distribution, the two-time correlation function and the average escape time, we find that the particle interaction, especially the resulted condensation, can significantly influence the dynamics. In the stationary state, both the average rest time and the average escape time caused by the attraction among particles are obtained analytically. In the transient state, a hierarchical nature of the aging dynamics is revealed by both simulations and scaling analysis. Moreover, by comparing the particle diffusion in both the transient state and the stationary state, we find that the closer ZRP systems approach the stationary state, the more slowly particles diffuse.

cond-mat.stat-mech↗

arXiv2011

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 proposed some efficient routing strategies that do not strictly obey the FIFO rule. Comparing with the routine shortest path strategy, the throughput for both Barabási-Albert (BA) networks and the real Internet, the throughput can be improved more than five times. We calculate the theoretical limitation of the throughput. In BA networks, our proposed strategy can achieve 88% of the theoretical optimum, yet for the real Internet, it is about 12%, implying that we have a huge space to further improve the routing strategy for the real Internet. Finally we discuss possibly promising ways to design more efficient routing strategies for the Internet.

physics.data-an↗

arXiv2010

Composite THz materials using aligned metallic and semiconductor microwires, experiments and interpretation

We report fabrication method and THz characterization of composite films containing either aligned metallic (tin alloy) microwires or chalcogenide As2Se3 microwires. The microwire arrays are made by stack-and-draw fiber fabrication technique using multi-step co-drawing of low-melting-temperature metals or semiconductor glasses together with polymers. Fibers are then stacked together and pressed into composite films. Transmission through metamaterial films is studied in the whole THz range (0.1-20 THz) using a combination of FTIR and TDS. Metal containing metamaterials are found to have strong polarizing properties, while semiconductor containing materials are polarization independent and could have a designable high refractive index. Using the transfer matrix theory, we show how to retrieve the complex polarization dependent refractive index of the composite films. We then detail the selfconsistent algorithm for retrieving the optical properties of the metal alloy used in the fabrication of the metamaterial layers by using an effective medium approximation. Finally, we study challenges in fabrication of metamaterials with sub-micrometer metallic wires by repeated stack-and-draw process by comparing samples made using 2, 3 and 4 consecutive drawings. When using metallic alloys we observe phase separation effects and nano-grids formation on small metallic wires.

physics.optics↗

arXiv2008

Detrended fluctuation analysis of traffic data

Different routing strategies may result in different behaviors of traffic on internet. We analyze the correlation of traffic data for three typical routing strategies by the detrended fluctuation analysis (DFA) and find that the degree of correlation of the data can be divided into three regions, i.e., weak, medium, and strong correlation. The DFA scalings are constants in both the regions of weak and strong correlation but monotonously increase in the region of medium correlation. We suggest that it is better to consider the traffic on complex network as three phases, i.e., the free, buffer, and congestion phase, than just as two phases believed before, i.e., the free and congestion phase.

cs.NI↗

arXiv2008

An adaptive routing strategy for packet delivery in complex networks

We present an efficient routing approach for delivering packets in complex networks. On delivering a message from a node to a destination, a node forwards the message to a neighbor by estimating the waiting time along the shortest path from each of its neighbors to the destination. This projected waiting time is dynamical in nature and the path through which a message is delivered would be adapted to the distribution of messages in the network. Implementing the approach on scale-free networks, we show that the present approach performs better than the shortest-path approach and another approach that takes into account of the waiting time only at the neighboring nodes. Key features in numerical results are explained by a mean field theory. The approach has the merit that messages are distributed among the nodes according to the capabilities of the nodes in handling messages.

cs.NI↗