Biomedical subjects

Bing-Hong Wang

Publications and source records attributed to Bing-Hong Wang.

17 recordsLinked to original sources

PubMed2006

Decoupling process for better synchronizability on scale-free networks.

We propose a decoupling process performed in scale-free networks to enhance the synchronizability of the network, together with preserving the scale-free structure. Simulation results show that the decoupling process can effectively promote the network synchronizability, which is measured in terms of eigenratio of the coupling matrix. Moreover, we investigate the correlation between some important structural properties and the collective synchronization, and find that the maximum vertex betweenness seems to be the most strongly correlated with the synchronizability among the major structural features considered. We explain the effect of the decoupling process from a viewpoint of coupling information transmission. Our work provides some evidence that the dynamics of synchronization is related to that of information or vehicle traffic. Because of the low cost in modifying the coupling network, the decoupling process may have potential applications.

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PubMed2006

Integrating local static and dynamic information for routing traffic.

The efficiency of traffic routing on complex networks can be reflected by two key measurements, i.e., the network capacity and the average travel time of data packets. In this paper we propose a mixing routing strategy by integrating local static and dynamic information for enhancing the efficiency of traffic on scale-free networks. The strategy is governed by a single parameter. Simulation results show that maximizing the network capacity and reducing the packet travel time can generate an optimal parameter value. Compared with the strategy of adopting exclusive local static information, the new strategy shows its advantages in improving the efficiency of the system. The detailed analysis of the mixing strategy is provided for explaining its effects on traffic routing. The work indicates that effectively utilizing the larger degree nodes plays a key role in scale-free traffic systems.

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PubMed2006

Efficient routing on complex networks.

We propose a routing strategy to improve the transportation efficiency on complex networks. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with the largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our strategy, can be redistributing traffic load in central nodes to other noncentral nodes. Simulation results indicate that the network capability in processing traffic is improved more than 10 times by optimizing the efficient path, which is in good agreement with the analysis.

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PubMed2006

Better synchronizability predicted by crossed double cycle.

In this Brief Report, we propose a network model named crossed double cycles, which are completely symmetrical and can be considered as the extensions of nearest-neighboring lattices. The synchronizability, measured by eigenratio R, can be sharply enhanced by adjusting the only parameter, the crossed length m. The eigenratio R is shown very sensitive to the average distance L, and the smaller average distance will lead to better synchronizability. Furthermore, we find that, in a wide interval, the eigenratio R approximately obeys a power-law form as R approximately L(1.5).

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PubMed2006

Traffic dynamics based on local routing protocol on a scale-free network.

We propose a packet routing strategy with a tunable parameter based on the local structural information of a scale-free network. As free traffic flow on the communication networks is key to their normal and efficient functioning, we focus on the network capacity that can be measured by the critical point of phase transition from free flow to congestion. Simulations show that the maximal capacity corresponds to alpha= -1 in the case of identical nodes' delivering ability. To explain this, we investigate the number of packets of each node depending on its degree in the free flow state and observe the power law behavior. Other dynamic properties including average packets traveling time and traffic load are also studied. Inspiringly, our results indicate that some fundamental relationships exist between the dynamics of synchronization and traffic on the scale-free networks.

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PubMed2006

Mutual attraction model for both assortative and disassortative weighted networks.

For most complex networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a mutual attraction model to characterize weighted evolving networks. By introducing the initial attractiveness A and the general mechanism of mutual attraction (controlled by parameter m), our model can naturally reproduce scale-free distributions of degree, weight, and strength, as found in many real systems. Also, simulation results are consistent with theoretical predictions. Interestingly, we obtain nontrivial clustering coefficient C and tunable degree assortativity r, depending on the values of m and A. Our model appears as a more general one that unifies the characterization of both assortative and disassortative weighted networks.

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PubMed2005

Advanced information feedback in intelligent traffic systems.

The optimal information feedback is very important to many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. As to traffic flow, a reasonable real-time information feedback can improve the urban traffic condition by providing route guidance. In this paper, the influence of a feedback strategy named congestion coefficient feedback strategy is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other two information feedback strategies, i.e., travel time and mean velocity.

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PubMed2005

Enhanced synchronizability by structural perturbations.

In this Brief Report, we investigate the collective synchronization of a system of coupled oscillators on a Barabási-Albert scale-free network. We propose an approach of structural perturbations aiming at those nodes with maximal betweenness. This method can markedly enhance the network synchronizability, and is easy to realize. The simulation results show that the eigenratio will sharply decrease by one-half when only 0.6% of those hub nodes occur under three-division processes when the network size . In addition, the present study also provides numerical evidence that the maximal betweenness plays a major role in network synchronization.

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PubMed2005

Self-organized Boolean game on networks.

A model of a Boolean game with only one free parameter p that denotes the strength of local interaction is proposed wherein each agent acts according to the information obtained from his neighbors in the network, and those in the minority are rewarded. The simulation results indicate that the dynamic of the system is sensitive to network topology, whereby the network of larger degree variance, i.e., the system of greater information heterogeneity, leads to less system profit. The system can self-organize to a stable state and perform better than the random choice game, although only the local information is available to the agents. In addition, in heterogeneity networks, the agents with more information gain more than those with less information for a wide extent of interaction strength p.

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PubMed2005

Mutual selection model for weighted networks.

For most networks, the connection between two nodes is the result of their mutual affinity and attachment. In this paper, we propose a mutual selection model to characterize the weighted networks. By introducing a general mechanism of mutual selection, the model can produce power-law distributions of degree, weight, and strength, as confirmed in many real networks. Moreover, we also obtained the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation depending on a single parameter m. These results are supported by present empirical evidence. Studying the degree-dependent average clustering coefficient C(k) and the degree-dependent average nearest neighbors' degree k(nn)(k) also provide us with a better description of the hierarchies and organizational architecture of weighted networks.

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PubMed2005

Continuous extremal optimization for Lennard-Jones clusters.

We explore a general-purpose heuristic algorithm for finding high-quality solutions to continuous optimization problems. The method, called continuous extremal optimization (CEO), can be considered as an extension of extremal optimization and consists of two components, one which is responsible for global searching and the other which is responsible for local searching. The CEO's performance proves competitive with some more elaborate stochastic optimization procedures such as simulated annealing, genetic algorithms, and so on. We demonstrate it on a well-known continuous optimization problem: the Lennard-Jones cluster optimization problem.

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PubMed2005

General dynamics of topology and traffic on weighted technological networks.

For most technical networks, the interplay of dynamics, traffic, and topology is assumed crucial to their evolution. In this Letter, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general strength-coupling mechanism under which the traffic and topology mutually interact, the model gives power-law distributions of degree, weight, and strength, as confirmed in many real networks. Particularly, depending on a parameter W that controls the total weight growth of the system, the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation are all consistent with empirical evidence.

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PubMed2005

Maximal planar networks with large clustering coefficient and power-law degree distribution.

In this article, we propose a simple rule that generates scale-free networks with very large clustering coefficient and very small average distance. These networks are called random Apollonian networks (RANs) as they can be considered as a variation of Apollonian networks. We obtain the analytic results of power-law exponent gamma=3 and clustering coefficient C= (46/3)-36 ln 3/2 approximately 0.74, which agree with the simulation results very well. We prove that the increasing tendency of average distance of RANs is a little slower than the logarithm of the number of nodes in RANs. Since most real-life networks are both scale-free and small-world networks, RANs may perform well in mimicking the reality. The RANs possess hierarchical structure as C(k) approximately k(-1) that are in accord with the observations of many real-life networks. In addition, we prove that RANs are maximal planar networks, which are of particular practicability for layout of printed circuits and so on. The percolation and epidemic spreading process are also studied and the comparisons between RANs and Barabási-Albert (BA) as well as Newman-Watts (NW) networks are shown. We find that, when the network order N (the total number of nodes) is relatively small (as N approximately 10(4)), the performance of RANs under intentional attack is not sensitive to N , while that of BA networks is much affected by N. And the diseases spread slower in RANs than BA networks in the early stage of the susceptible-infected process, indicating that the large clustering coefficient may slow the spreading velocity, especially in the outbreaks.

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PubMed2005

Power law distribution of wealth in population based on a modified Equíluz-Zimmermann model.

We propose a money-based model for the power law distribution (PLD) of wealth in an economically interacting population. It is introduced as a modification of the Equíluz and Zimmermann (EZ) model for crowding and information transmission in financial markets. Still, it must be stressed that in the EZ model a PLD without exponential correction is obtained only for a particular parameter, while our pattern will give the exact PLD within a wide range. The PLD exponent depends on the model parameters in a non-trivial way and is exactly calculated in this paper. The numerical results are in excellent agreement with the analytic prediction, and also comparable with empirical data of wealth distribution.

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PubMed2004

Adiabatic theory for the population distribution in the evolutionary minority game.

We study the evolutionary minority game (EMG) using a statistical mechanics approach. We derive a theory for the steady-state population distribution of the agents. The theory is based on an "adiabatic approximation" in which short time fluctuations in the population distribution are integrated out to obtain an effective equation governing the steady-state distribution. We discover the mechanism for the transition from segregation (into opposing groups) to clustering (towards cautious behaviors). The transition is determined by two generic factors: the market impact (of the agents' own actions) and the short time market inefficiency (arbitrage opportunities) due to fluctuations in the numbers of agents using opposite strategies. A large market impact favors "extreme" players who choose fixed opposite strategies, while large market inefficiency favors cautious players. The transition depends on the number of agents (N) and the effective rate of strategy switching. When N is small, the market impact is relatively large; this favors the extreme behaviors. Frequent strategy switching, on the other hand, leads to a clustering of the cautious agents.

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PubMed2002

Cellular automata model simulating traffic interactions between on-ramp and main road.

In this paper, we study the on-ramp system using the cellular automata traffic flow model. Different from previous works, we consider not only the influence of the on-ramp flow on the main road but also the opposite influence. The update rules are given in detail and the concept of priority is introduced. The numerical simulations are carried out and the phase diagram is presented. Two different types of phase diagram are distinguished and the currents of the on-ramp system are discussed.

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PubMed2002

Finite-size effect in the Eguíluz and Zimmermann model of herd formation and information transmission.

The Eguíluz and Zimmermann model of information transmission and herd formation in a financial market is studied analytically. Starting from a formal description on the rate of change of the system from one partition of agents in the system to another, a mean-field theory is systematically developed. The validity of the mean-field theory is carefully studied against fluctuations. When the number of agents N is sufficiently large and the probability of making a transaction a<<1/N ln N, finite-size effect is found to be significant. In this case, the system has a large probability of becoming a single cluster containing all the agents. For small clusters of agents, the cluster size distribution still obeys a power law but with a much reduced magnitude. The exponent is found to be modified to the value of -3 by the fluctuation effects from the value of -5/2 in the mean-field theory.

Cluster Analysis↗