车载自组织网络中基于蚁群算法的簇路由协议

由于车辆的高速移动及拓扑动态变化,构建稳定的传输路径是车载自组织网络VANETs(Vehicular ad hoc Networks)应用的关键。而簇技术建立稳定传输路径的有效技术之一。为此,提出基于蚁群算法的簇路由ACCR(Ant Colony algorithm based cluster routing)协议。蚁群系统是典型的启发性算法,能够解决簇划分问题。据此,ACCR协议利用蚁群算法选择簇头,提高簇的稳定性和数据传输性能。仿真结果表明,与ACO-CR协议相比,提出的ACCR协议的簇头寿命提高了近20%,数据传输率提高了近45%。     

Competitive cluster growth on networks: Complex dynamics and survival strategies

We extend the study of a model of competitive cluster growth in an active medium from a regular topology to a complex network topology; this is done by adding nonlocal connections with probability p to sites on a regular lattice, thus enabling one to interpolate between regularity and full randomness. The model on networks demonstrates high sensitivity to small changes in initial configurations, which we characterize using damage spreading. The main focus of this paper is, however, the devising of survival strategies through selective networking, to alter the fate of an arbitrarily chosen cluster: whether this be to revive a dying cluster to life, or to make a weak survivor into a stronger one. Although such goals are typically achieved by networking with relatively small clusters, our results suggest that it ought to be possible also to network successfully with peers and larger clusters. The main indication of this comes from the probability distributions of mass differences between survivors and their immediate neighbours, which show an interesting universality; they suggest strategies for winning against the odds.     

Molecular dynamics study of particle emission by reactive cluster ion impact

Molecular dynamics (MD) simulations of sputtering process with fluorine cluster impact onto silicon targets were performed. By iterating collisional simulations on a same target, accumulation of incident atoms and evolution of surface morphology were examined as well as emission process of precursors. When (F₂)₃₀₀ clusters were sequentially irradiated on Si(1 0 0) target at 6 keV of total incident energy, column-like surface structure covered with F atoms was formed. As the number of incident clusters increased, sputtering yield of Si atoms also increased because the target surface was well fluoridised to provide SiF_x precursors. Size distribution of emitted particles showed that SiF₂ was the major sputtered particle, but various types of silicon-fluoride compounds such like Si₂F_x, Si₃F_x and very large molecules consists of 100 atoms were also observed. This size distribution and kinetic energy distribution of desorbed materials were studied, which showed that the sputtering mechanism with reactive cluster ions is similar to that under thermal equilibrium condition at high-temperature.     

Formation of argon cluster with proton seeding

ABSTRACT

We employ force-field molecular dynamics simulations to investigate the kinetics of nucleation to new liquid or solid phases in a dense gas of particles, seeded with ions. We use precise atomic pair interactions, with physically correct long-range behaviour, between argon atoms and protons. Time dependence of molecular cluster formation is analysed at different proton concentration, temperature and argon gas density. The modified phase transitions with proton seeding of the argon gas are identified and analysed. The seeding of the gas enhances the formation of nano-size atomic clusters and their aggregation. The strong attraction between protons and bath gas atoms stabilises large nano-clusters and the critical temperature for evaporation. An analytical model is proposed to describe the stability of argon-proton droplets and is compared with the molecular dynamics simulations.     

Cu87团簇在升温与急冷过程中结构变化的原子尺度模拟

本文采用基于嵌入原子法的正则系综分子动力学方法在原子尺度上计算了包含87个原子的Cu87金属团簇在连续升温和急冷降温时的结构演化过程。根据原子平均势能、对分布函数、原子堆积结构和主要原子键对数目随温度的变化表明,温度的不同极大地影响团簇内的原子堆积结构。在升温过程中,随着温度的升高,团簇内原子堆积结构出现由密排六方、二十面体直到无序堆积的变化。在急冷降温过程中,随着急冷温度的降低,团簇内由出现的一定数量的二十面体和面心立方的局域结构、数量不一的HCP,FCC和二十面体局域结构,直到急冷温度较低时的一定数量的二十面体局域结构。     

Modeling the social obesity epidemic with stochastic networks

In this paper we extend a compartmental model to the case of a homogenous network epidemic model for a study of the dynamics of obese populations. The social epidemic network-based approach developed here uses different algorithms and points of views regarding the simulation of the dynamics of the network. First, Monte Carlo simulations for homogeneous networks using a traditional constant probability transition rates and a mean-field-like approach are presented. We show that these networks evolve towards an approximately stationary state, which coincides with the one obtained by the underlying classical compartmental continuous model. A mean-field-like approach is applied in order to reduce the large computation time required when dealing with large contact networks. We also investigate, using homogenous contact networks, the effect of the realistic assumption that the waiting times between subpopulations follow a gamma distribution instead of the traditional exponential distribution. It is concluded that careful attention must be paid to the distributions assumed for the state periods.     

Modelling spikes in electricity markets using excitable dynamics

We present a general methodology to model spikes in deregulated electricity markets using excitable dynamics in a multi-regime switching approach. In particular, we propose a two-regime switching model and a three-regime switching model in which the spikes phenomenon is described by a FitzHugh-Nagumo excitable dynamics. Both models seems to be interesting candidates for describing the main characteristics of electricity price dynamics as the occurrence of stable periods in which prices fluctuate around some long-run mean, and turbulent periods in which prices experience jumps and spikes of very large magnitude. In agreement with market data, both models can produce probability distributions of price returns with positive skewness and very high values of kurtosis.     

Opinion dynamics in networks with heterogeneous confidence and influence

We propose a discrete-time model of opinion dynamics. The neighborhood relationship is decided by confidence radius and influence radius of each agent. We investigate the influence of heterogeneity in confidence/influence distribution on the behavior of the network. The simulations suggest that the heterogeneity of single confidence or influence networks can promote the opinions to achieve consensus. It is shown that the heterogeneous influence radius systems converge in fewer time steps and more often in finite time than the heterogeneous confidence radius systems. We find that heterogeneity does not always promote consensus, and there is an optimal heterogeneity so that the relative size of the largest consensus cluster reaches maximum in heterogeneous confidence and influence networks.     

几何构型不同的Na团簇碰撞动力学研究

采用距离相关紧密束缚的分子动力学模型,在不同碰撞能量以及不同的碰撞参数下,研究了两种构型的Na6(2D),Na6(3D)与Na8团簇间的碰撞.讨论了反应机制的变化,即全融合、深度非弹、非弹性碰撞过程.结果表明:构型不同的团簇与相同的靶碰撞显示了不同的特征.低能时Na6(3D)易融合;DIC反应时,易于形成大的团簇 关键词： Na团簇 原子团簇碰撞 紧束缚模型     

Dominant vertices in regulatory networks dynamics

Discrete-time regulatory networks are dynamical systems on directed graphs with a structure that is inspired on natural systems of interacting units. Using a notion of determination between vertices, we define sets of dominant vertices, and we prove that in the asymptotic regime, the projection of the dynamics on a dominant set allows us to determine the state of the whole system at all times. We provide an algorithm to find sets of dominant vertices, and we test its accuracy on several examples. We also explore the possibility of using the dominant set characteristics as a measure of the structural complexity of networks.     

金属钛中氦团簇生长行为的分子动力学研究

运用分子动力学方法模拟了常温下金属钛中氦团簇的生长过程.从能量的角度考察了氦团簇的生长机理.研究发现,随着氦团簇的生长,在氦团簇周围逐渐形成位错环缺陷,氦团簇与氦原子的结合能有逐渐下降的趋势,当氦团簇生长到一定尺寸时会通过发射周围缺陷以使得结合能上升,从而增强了进一步吸收氦原子的能力.模拟还发现,随着氦团簇的继续生长,氦团簇的形状由原来的不规则结构逐渐变成了较为规则的棱柱形结构,在随后的生长过程中其生长仅在（001）平面进行,沿［001］轴的厚度几乎不变. 关键词： 氦团簇 缺陷发射 分子动力学模拟     

Impact and spreading behavior of cluster atoms bombarding substrates

The purpose of this study is to investigate the behavior of copper cluster atoms bombarding a substrate using molecule dynamics based on tight-binding second moment approximation (TB-SMA) potential. The simulated results show that a crater on the substrate surface was created by the impact of the clusters. The variations of kinetic energy of cluster bombardments can be divided into three stages. At the initial impact level, the kinetic energies of the clusters and the substrate were constant. Then, the system went into a sluggish stage of energy variation, in which the kinetic energy of the clusters reduced. In the final stage, the kinetic energy of the system became stable. The high slip vector region around the crater had a disorder damage zone. The symmetry-like cross-slip occurred beneath the top layer of the substrate along the 〈1 1 0〉 orientations. The spreading index, temperature, and potential functions that affect the bombardments are also discussed.     

Rhythm dynamics of complex neuronal networks with mixed bursting neurons

The spatiotemporal order and rhythm dynamics of a complex neuronal network with mixed bursting neurons are studied in this paper. A quantitative characteristic, the width factor, is introduced to describe the rhythm dynamics of an individual neuron, and the average width factor is used to characterize the rhythm dynamics of a neuronal network. An r parameter is introduced to denote the ratio of the short bursting neurons in the network. Then we investigate the effect of the ratio on the rhythm dynamics of the neuronal network. The critical value of r is derived, and the neurons in the network always remain short bursting when the r ratio is larger than the critical value.     

Traffic dynamics in scale-free networks with tunable strength of community structure

In this paper we systematically investigate the impact of community structure on traffic dynamics in scale-free networks based on local routing strategy. A growth model is introduced to construct scale-free networks with tunable strength of community structure, and a packet routing strategy with a parameter α is used to deal with the navigation and transportation of packets simultaneously. Simulations show that the maximal network capacity stands at α=−1 in the case of identical vertex capacity and monotonously decreases with the strength of community structure which suggests that the networks with fuzzy community structure (i.e., community strength is weak) are more efficient in delivering packets than those with pronounced community structure. To explain these results, the distribution of packets of each vertex is carefully studied. Our results indicate that the moderate strength of community structure is more convenient for the information transfer of real complex systems.     

Chaotic dynamics of high-order neural networks

The dynamics of an extremely diluted neural network with high-order synapses acting as corrections to the Hopfield model is investigated. The learning rules for the high-order connections contain mixing of memories, different from all the previous generalizations of the Hopfield model. The dynamics may display fixed points or periodic and chaotic orbits, depending on the weight of the high-order connections , the noise levelT, and the network load, defined as the ratio between the number of stored patterns and the mean connectivity per neuron, =P/C. As in the related fully connected case, there is an optimal value of the weight that improves the storage capacity of the system (the capacity diverges).     

无标度网络上的传播动力学

介绍了无标度网络上的传播动力学,在susceptible-infected-susceptible（SIS）模型的基础上考察了一般情况下无标度网络中疾病爆发的临界点问题,得出了关于临界点一般性的表达式.得到的结果在特殊情况下分别退化为已有的一些经典结论.同时分别讨论了这些情况的建模意义和可靠性. 关键词： 无标度网络 传播动力学 susceptible-infected-susceptible模型 临界点     

Random pseudofractal scale-free networks with small-world effect

A random pseudofractal network (RPN) is generated by a recursive growing rule. The RPN is of the scale-free feature and small-world effect. We obtain the theoretical results of power-law exponent γ=3, clustering coefficient C=3π²-19≈ 0.74, and a proof that the mean distance increases no faster than ln N, where N is the network size. These results agree with the numerical simulation very well. In particular, we explain the property of growth and preferential attachment in RPNs. And the properties of a class of general RPNs are discussed in the end.