Revealing the process of edge-based-attack cascading failures

In this paper, concerned with the highest-load attack (HL) and random attack (RA) on one edge or one node, we model the cascading dynamics in scale-free networks (SF), WS small-world networks (WS) and ER random networks (ER). How long the cascade propagation in networks will persist and what features the avalanche edges or nodes at each time step will show in cascading failures are questions investigated. We find that, under both HL and RA attack, the persistent time of cascade propagation in SF networks is always longer than in ER and WS networks (except p=0.1). Under HL attack, there exists a threshold ?? _c of tolerance parameter ?? making the cascading propagation in SF and WS networks longest-running. Moreover, under HL attack, the avalanche edges and nodes in WS and ER networks always reach a peak over a period of time, while the SF network shows similar characteristics only in some field of ??. However, under RA attack, in the case of big ??, most of the avalanche edges and nodes in SF, WS and ER networks always occur at the beginning of the cascading failures. Furthermore, under node-targeted attack, SF shows to be more vulnerable than under edge-targeted attack and most of avalanche nodes occur at the beginning of failures. The results remind us to grasp the rhythm of controlling disasters according to the features of cascading failures in different networks.     

Attack robustness of cascading model with node weight

Considering the node weight and the effect of the neighboring nodes, we introduce a method to define the initial load of a node in a network and propose a cascading model. Our aim is to explore how to allocate the initial load and select some nodes to be protected so as to maximize the network robustness against cascading failures. According to the distribution of the node weight and the normalized effect of the neighboring nodes, we focus on investigating different roles of high-load and low-load nodes and the correlation between some parameters in our model and the strongest robust level of a network against cascading failures. We obtain by the numerical simulations the optimal values of the parameters in our model at which the network can reach the strongest robust level against cascading failures. In addition, we find that the effect of two attacks strongly depends on the parameters of the node weight and the normalized effect of the neighboring nodes, i.e., the network robustness of attacking the low-load nodes has a positive correlation with the parameter of the node weight, while has a negative correlation with the parameter of the normalized reaction of the neighboring nodes. While the result of attacking the high-load nodes is almost on the contrary. Finally, we verify the numerical results by the theoretical analysis.     

Modeling and analysis of under-load-based cascading failures in supply chain networks

Nonlinear Dynamics - The phenomena of cascading failures often happen in complex networks. In most infrastructure networks, the subsequent failures of nodes are caused by overload and many overload...     

Pinning synchronization of weighted complex networks with variable delays and adaptive coupling weights

In this paper, the synchronization for time-delayed complex networks with adaptive coupling weights is studied. A pinning strategy and a local adaptive scheme to determine coupling weights and feedback gains are proposed. It is noted that our control strategies only rely on some local information other than the global information of the whole network. Finally, the developed techniques are applied to two complex networks which are respectively synchronized to an unstable equilibrium point and a chaotic attractor.     

Nonlinear dynamic evolution and control in a new scale-free networks modeling

The nonlinear evolving and controlling in complex networks are an important way to understand the dynamic mechanism for real networks. In order to explore universality of scale-free systems, we propose an extended network model based on Barabási–Albert model by developing and decaying networks. The novel network evolves by growing and optimizing processes, such as the addition of new nodes and edges, or deletion of edges at every time step. Meanwhile, in order to describe more realistic phenomena of reality, we introduce the fitness to reflect the competition and local event of inner anti-preferential mechanism to delete the edges. We calculate analytically the degree distribution and find that the Barabási–Albert model is only one of its special cases and the model self-organizes into scale-free networks, moreover, the numerical simulations are in good agreement with the analytical conclusions. The results imply that this extended model has more comprehensive and universal simulation and reflection in complex network topology characters and evolution with practices and applications.     

A simulation of the cascading failure of a complex network model by considering the characteristics of road traffic conditions

Using the dual method, we start with a traditional road traffic network with a constructed logic network with small-world characteristics and construct the complex network of road traffic. After analyzing and comparing with other complex networks, the time delay, restorative, and other characteristics are presented for the complex network of road traffic, and then, the cascading failure model of the complex network is simulated. The simulation results show that using different time delays, an incident dissipation factor and load capacity can reasonably avoid a cascading failure, and they can remove its effects. In addition, our results provide value and guidance for building a road traffic network that prevents and removes the cascading failure of a road network.

     

Noise-induced outer synchronization between two different complex dynamical networks

In this paper, based on the theory of stochastic differential equations, we study the outer synchronization between two different complex dynamical networks with noise coupling. The theoretical result shows that two different complex networks can achieve generalized outer synchronization only with white-noise-based coupling. Numerical examples further verify the effectiveness and feasibility of the theoretical results. Numerical evidence shows that the synchronization rate is proportional to the noise intensity.     

An SIR model with infection delay and propagation vector in complex networks

Based on the SIR (Susceptible-Infected-Removed) model, we propose a novel epidemic model to investigate the impact of infection delay and propagation vector on the spreading behaviors in complex networks. Mean-field approximations and extensive numerical simulations indicate that the infection delay and propagation vector can largely reduce the critical threshold and promote the outbreak of epidemics, and even lead to the case that the infectious diseases transform from the disease-free state to endemic one. The current results are greatly instructive for us to further understand the epidemic spreading and design some effective prevention and containment strategies to fight the epidemics.     

THE PARALLEL BLOCK ADAPTIVE MULTIGRID METHOD FOR THE IMPLICIT SOLUTION OF THE EULER EQUATIONS

A method capable of solving very fast and robust complex non-linear systems of equations is presented. The block adaptive multigrid (BAM) method combines mesh adaptive techniques with multigrid and domain decomposition methods. The overall method is based on the FAS multigrid, but instead of using global grids, locally enriched subgrids are also employed in regions where excessive solution errors are encountered. The final mesh is a composite grid with uniform rectangular subgrids of various mesh densities. The regions where finer grid resolution is necessary are detected using an estimation of the solution error by comparing solutions between grid levels. Furthermore, an alternative domain decomposition strategy has been developed to take advantage of parallel computing machines. The proposed method has been applied to an implicit upwind Euler code (EuFlex) for the solution of complex transonic flows around aerofoils. The efficiency and robustness of the BAM method are demonstrated for two popular inviscid test cases. Up to 19-fold acceleration with respect to the single-grid solution has been achieved, but a further twofold speed-up is possible on four-processor parallel computers.     

Adaptive inverse control of variable speed wind turbine

The efficiency and reliability of wind power has been shown to be depending on the applied control strategy of the wind turbine. In this paper, an adaptive control strategy is proposed for variable speed wind turbine (VSWT), producing energy limitation above rated wind speed. In the proposed control strategy, the process is modeled using a neural networks based identifier, providing the sensitivity information of the process to the control input. Another neural networks is employed as an inverse model controller established via inverse system method. These two neural networks are off-line learned firstly and are on-line updated using the back propagation algorithm. Simulation results have shown the effectiveness of the proposed adaptive control strategy.     

Improving synchronous ability between complex networks

We investigate the synchronization ability between complex networks and propose a near optimal connection strategy based on one connection. Numerical simulations on scale-free, small-world and random network are presented to prove the effectiveness of the proposed strategy. Furthermore, we find that the synchronization ability of the networks can be improved more largely by enhancing inter-network coupling strength than by enhancing intra-network coupling strength. We find that there is an upper limit for the synchronization ability of the complex networks, and we analyze the corresponding reason.     

复杂网络的同步: 理论、方法、应用与展望

复杂网络随处可见, 如互联网、电力网络、商业网络、生物神经网络、社会关系网等. 这些复杂网络与我们的生活息息相关, 对它们的深入研究不但会促进许多重要科学分支的发展而且可能引起人类社会生活方式的根本变革. 同步是自然界中广泛存在的一类非常重要的非线性现象, 复杂网络展示了丰富多彩的网络同步现象. 在过去10年里, 不同研究领域的学者从不同的角度广泛而深入地开展了复杂网络同步的研究. 本文简要的回顾国内外过去10年在复杂网络同步领域的主要研究进展, 包括理论、方法、应用与展望, 试图推进国内复杂网络同步的研究.      

A mixing propagation model of computer viruses and countermeasures

Based on the CMC antivirus strategy proposed by Chen and Carley, a mixing propagation model of computer viruses and countermeasures is suggested. This model has two potential virus-free equilibria and two potential endemic equilibria. The existence and global stability of these equilibria are fully investigated. From the obtained results it can be deduced that the CMC strategy is efficacious in deracinating viruses.     

Performance measures for targeted energy transfer and resonance capture cascading in nonlinear energy sinks

In vibrating mechanical systems, the targeted energy transfer mechanism (TET) of nonlinear energy sinks (NES) is employed as an alternative to linear tuned mass dampers (TMD) as passive vibrations absorbers for transient vibrations. The major advantages a NES has over a linear TMD are (1) an increased robustness to detuning and (2) the ability to dissipate multiple frequencies with only a single NES through so-called resonance capture cascading (RCC). The performance, especially the speed, of TET and RCC has rarely been a topic of research. In this research, algebraic performance measures for the speed of both TET and RCC are derived, called the pumping time and the cascading time, respectively. It shows that cascading time can be seen as a sum of single-mode pumping times, by introducing a novel modal decomposition. The strength of both measures is that they do not require numerical simulations, allowing easy optimization of the NES. The influence of different nonlinearities on the TET and RCC performance is investigated. Actual numerical simulations presented in the study validate the merit of both the pumping time and cascading time.     

Hybrid genetic algorithms and artificial neural networks for complex design optimization in CFD

The present paper is devoted to the study of design optimization strategies in the particular framework of complex computational fluid dynamics. Genetic algorithms are chosen as the optimization strategy, thanks to their robustness and flexibility. Two ways are explored to improve the behaviour of genetic algorithms in order to increase the efficiency of the search. First, approximated pre‐evaluations based on artificial neural networks are used to benefit from the knowledge acquired from the problem and to reduce the number of expensive evaluations by the flow solver required at each generation. Then, a hybridization technique is proposed for the final local search, which is performed by a deterministic method. These approaches are validated and applied on two‐ and three‐dimensional problems, involving Reynolds‐averaged Navier–Stokes computations with near‐wall turbulence modeling. Copyright © 2004 John Wiley & Sons, Ltd.     

Adaptive synchronization of T-S fuzzy complex networks with time-varying delays via the pinning control method

In this paper, the synchronization of Takagi–Sugeno (T-S) fuzzy complex networks with time-varying delays and adaptive coupling weights is studied. Using the pinning control and adaptive feedback strategy, a new general class of complex networks with fuzzy logic is proposed and its synchronization is investigated in terms of linear matrix inequalities (LMIs). The adaptive update law of coupling weight is only related to the dynamical behaviors of directly connected nodes. Based on the Lyapunov stability theory, it is proven that the synchronization of the addressed network can be achieved under those control strategies. Finally, two numerical examples are given to verify the effectiveness of our theoretical results.     

复杂动态网络传播动力学

病毒、谣言、舆论等在现实社会中各种复杂网络系统上的传播现象与人们现代社会经济生活息息相关,对复杂网络上各种传播现象的动力学行为研究是复杂网络理论的一个重要命题.从流行病学的角度, 针对复杂网络传播行为中存在的动态过程,从自适应躲避、响应时滞、离散采样、开放式系统增长等方面综述了复杂网络传播动力学研究的若干进展.      

Pinning synchronization of complex directed dynamical networks under decentralized adaptive strategy for aperiodically intermittent control

In this paper, the problem of global synchronization for complex directed dynamical networks via adaptive aperiodically intermittent pinning control is studied. By constructing a piecewise Lyapunov function, some sufficient conditions to guarantee global synchronization are derived based on the analytical technique and theory of series with nonnegative terms. Different from previous works, the adaptive intermittent pinning control is aperiodic with non-fixed both control period and control width, and moreover, the adaptive approach is decentralized relying only on the state information of the controlled node. Hence, the adaptive intermittent pinning control strategy proposed in this paper is more practically applicable than those in previous works. Additionally, it is noted that the derived synchronization criteria are dependent on the control rates, but not the control widths or the control periods, which makes the theoretical results are less conservative than the corresponding results given in the existing works. A numerical example is finally provided to illustrate the validity of our theoretical results.     

基于自适应多可信度多项式混沌-Kriging模型的高效气动优化方法

多可信度代理模型已经成为提高基于代理模型的优化算法效率和可信度水平最有效的手段之一.然而目前流行的co-Kriging和分层Kriging (HK)等多可信度代理模型泛化能力不足,缺乏对高阶/高非线性建模问题的适应性,难以广泛应用.文章基于发展的自适应多可信度多项式混沌-Kriging (MF-PCK)代理模型,在提高建模效率和对高阶/高非线性问题近似准确率的同时,建立了基于该自适应MF-PCK模型的高效全局气动优化方法.在发展的方法中,提出了基于MF-PCK模型的新型变可信度期望改进加点方法,使代理优化算法效率进一步提高.为了验证发展方法的全面表现,将其应用在经典的数值函数算例以及多个跨音速气动外形的确定性优化和稳健优化设计中,并与基于Kriging和HK模型的代理优化算法进行了全面比较.结果表明,发展的新型多可信度全局气动优化方法其优化效率相对于基于Kriging和HK模型的优化效率显著提高,结果更好也更加可靠,并且稳健优化设计效率和结果也更符合工程应用需求,证明了其相对于基于Kriging和HK模型的代理优化算法的显著优势.     

Failure-tolerant control for small agile satellites using single-gimbal control moment gyros and magnetic torquers

This paper focuses on the attitude control problem of small agile satellites using single-gimbal control moment gyros(CMG) and magnetic torquers(MTQ).CMGs are regarded as effective torque generators for agile satellites because of their torque amplification capability.However,they are vulnerable to failure due to their complex inner mechanism.In this paper,different failure cases of CMGs are analyzed.A flexible failure-tolerant control strategy is developed by automatically redistributing the required control torque among the operating CMGs and MTQs,with a variable limiter to accommodate the actuator dynamics changes introduced by CMG failures.The performances of maneuvers about different directions under different failure cases are also discussed and examined.Numerical simulations demonstrate that the proposed strategy maintains certain agility in the cases of one or two CMGs failing.Moreover,a survival strategy with only one CMG left is also verified.Both sun-pointing stabilization and earth-pointing stabilization can be achieved in this case,which fulfill some basic mission requirements.