基于逻辑器件响应特性的自治布尔网络调控

自治布尔网络已成功应用于随机数产生、基因调控、储备池计算等领域.为了在应用中合理选择器件使输出更好地满足各应用的需求,本文研究了自治布尔网络中的逻辑器件响应特性变化时,自治布尔网络输出状态随之变化的规律,结果显示逻辑器件响应特性变化可以调控自治布尔网络输出在周期和混沌之间转变,且能改变自治布尔网络输出序列的复杂程度.进一步观察了逻辑器件响应特性和链路延时二维参数空间中输出序列复杂程度的分布,结果显示快的逻辑门响应特性可以增强高复杂序列在链路延时参数空间的分布范围.同时研究了自治布尔网络中任意逻辑器件的响应特性单独变化对网络输出状态的影响,结果显示不同节点的器件响应特性对序列复杂程度的调控能力有差异.研究表明,逻辑器件响应特性可以调控网络输出序列复杂程度,快的响应特性有利于高复杂混沌的稳定产生.     

复杂网络中带有应急恢复机理的级联动力学分析

提出带有应急恢复机理的网络级联故障模型,研究模型在最近邻耦合网络,Erdos-Renyi随机网络,Watts-Strogatz小世界网络和Barabasi-Albert无标度网络四种网络拓扑下的网络级联动力学行为.给出了应急恢复机理和网络效率的定义,并研究了模型中各参数对网络效率和网络节点故障率在级联故障过程中变化情况的影响.结果表明,模型中应急恢复概率的增大减缓了网络效率的降低速度和节点故障率的增长速度,并且提高了网络的恢复能力.而且网络中节点负载容量越大,网络效率降低速度和节点故障率的增长速度越慢.同时,随着节点过载故障概率的减小,网络效率的降低速度和节点故障率的增长速度也逐渐减缓.此外,对不同网络拓扑中网络效率和网络节点故障率在级联故障过程中的变化情况进行分析,结果发现网络拓扑节点度分布的异质化程度的增大,提高了级联故障所导致的网络效率的降低速度和网络节点故障率的增长速度.以上结果分析了复杂网络中带有应急恢复机理的网络级联动力学行为,为实际网络中级联故障现象的控制和防范提供了参考.     

三阶多粒度光交叉连接的优化设计研究

在采用密集波分复用技术的骨干网中,通过建立动态多粒度业务模型对由大粒度（光纤和波带）和小粒度（波长）组成的三阶多粒度光交叉连接所构成的节点的网络特性（阻塞概率和带宽阻塞比）进行了研究和仿真分析，并由此对三阶多粒度节点的结构参数和网络中的系统参数进行了优化设计.从仿真结果可以看出，所提出来的优化设计方案能够显著的减少节点结构的复杂度并改善阻塞性能，从而减小了网络中设备的规模和成本.     

复杂网络可控性的研究概况

 近年来,随着复杂网络研究的不断深入,人们越来越关注于对复杂网络终极目标的探索,即如何对复杂网络进行控制。如同一辆构造精密且复杂的汽车,人们对汽车的驾驶和操控只需通过档位、油门、刹车和离合这样几个简单的部件即可(如图1 所示),那么对于一个节点连边众多的网络,我们也希望通过少量的外界输入来控制整个网络的运行状态,使网络的运行结果为我们所用。例如在电力网络中,如何对个别节点进行外界输入来达到调控整个网络的性能;在基因网络中,如何有选择地对某些节点进行外界输入或者干预来达到调控整个基因网络,从根本上实现对一些疾病的治愈等。     

基于节点健康度的无线传感器网络冗余通路控制方法

广泛应用于各种物理参数测量领域的无线传感器网络,因其节点具有能量供应有限、硬件资源有限、数目众多、自组织和动态拓扑等特点,使得网络极易发生故障,从而高可靠、低故障是其运行的基本要求.本文针对多冗余通路设计的无线传感器网络故障预防方法存在工作状态冗余节点过多、能量大量浪费的问题,提出一种基于节点健康度的冗余通路控制方法.该方法利用汇聚节点收集网络内所有节点能量状态,计算节点健康度等相关参数,使用A-Star算法选择最优工作通路,控制其余冗余通路分批轮流休眠,从而达到减少和均衡网络工作过程能量消耗、预防某些节点能量提前耗尽导致网络能量故障发生的目的.仿真实验和实际节点实验的结果表明,在保证网络适当冗余通路的前提下,与其他相关方法比较,该方法可以显著均衡网络能量消耗,有效预防节点能量故障提前发生,明显延长网络寿命.     

基于局部序参数的电网同步性能优化

采用类Kuramoto模型对电网中的节点进行建模,利用局部序参数描述节点的局部同步能力.研究发现相比小功率节点,大功率节点到其直接邻居节点更难达到同步.提出一种网络耦合强度的非均匀分配方法,在网络总耦合强度不变的情况下,增大大功率节点到其直接邻居节点的耦合强度以及相关节点对之间的连边耦合强度,减少其余节点对间的耦合强度.研究表明,这种方法可以在一定范围内降低电网的同步临界耦合强度,改善网络的同步性能;但当这种耦合强度的非均匀性过大时,网络的同步性能开始恶化.     

单向耦合网络连接的Lorenz系统的追踪控制

基于Lyapunov稳定性理论，将单个Lorenz系统的一种追踪控制方案用于单向耦合网络连接的Lorenz系统. 只对网络系统的一个节点加入控制器，就实现了单向耦合网络连接的Lorenz系统的单个输出变量对任意给定参考信号的追踪. 数值仿真表明，当网络的耦合强度足够大时，可以实现包括同结构和异结构系统信号之间的有效追踪. 关键词： Lorenz混沌系统 复杂动态网络 追踪控制 单向耦合     

花簇分形无标度网络中节点影响力的区分度

大量研究表明分形尺度特性广泛存在于真实复杂系统中, 且分形结构显著影响网络上的传播动力学行为. 虽然复杂网络的节点传播影响力吸引了越来越多学者的关注, 但依旧缺乏针对分形网络结构的节点影响力的系统研究. 鉴于此, 本文基于花簇分形网络模型, 研究了分形无标度结构上的节点传播影响力. 首先, 对比了不同分形维数下的节点影响力, 结果表明, 当分形维数很小时, 节点影响力的区分度几乎不随节点度变化, 很难区分不同节点的传播影响力, 而随着分形维数的增大, 从全局和局域角度都能很容易识别网络中的超级传播源. 其次, 通过对原分形网络进行不同程度的随机重连来分析网络噪声对节点影响力区分度的影响, 发现在低维分形网络上, 加入网络噪声之后能够容易区分不同节点的影响力, 而在无穷维超分形网络中, 加入网络噪声之后能够区分中间度节点的影响力, 但从全局和局域角度都很难识别中心节点的影响力. 所得结论进一步补充、深化了基于花簇分形网络的节点影响力研究, 研究结果对实际病毒传播的预警控制提供了一定的理论借鉴.     

基于最优调谐液柱阻尼器的气浮光学平台稳定性研究

为了解决气浮光学平台在水平方向超低频减振的问题以提高超精密实验的产出质量,提出基于调谐液柱阻尼器(TLCD)的气浮光学平台流固耦合理论,用来实现最优调谐控制和实验精度的提升.首先对TLCD进行原理分析并推导出固有频率的设计范围;其次对TLCD气浮光学平台流固耦合系统进行建模及推导;接着对流固耦合系统进行响应特性分析及参数优化;最后对时域响应和光学实验进行验证分析.结果 表明,当固有频率比一定时,存在一个最优阻尼比可以使减振效率取得最大值,共振峰处的减振效率达到66.76％;同时通过调控小孔板可以使TLCD减振系统适合宽频激励的工况,气浮光学平台动力响应的有效控制有利于提高实验精度,为超精密实验品质的提升提供了一种有效控制手段.     

多层单向耦合星形网络的特征值谱及同步能力分析

随着复杂网络同步的进一步发展,对复杂网络的研究重点由单层网络转向更加接近实际网络的多层有向网络.本文分别严格推导出三层、多层的单向耦合星形网络的特征值谱,并分析了耦合强度、节点数、层数对网络同步能力的影响,重点分析了层数和层间中心节点之间的耦合强度对多层单向耦合星形网络同步能力的影响,得出了层数对多层网络同步能力的影响至关重要.当同步域无界时,网络的同步能力与耦合强度、层数有关,同步能力随其增大而增强;当同步域有界时,对于叶子节点向中心节点耦合的多层星形网络,当层内耦合强度较弱时,层内耦合强度的增大会使同步能力增强,而层间叶子节点之间的耦合强度、层数的增大反而会使同步能力减弱;当层间中心节点之间的耦合强度较弱时,层间中心节点之间的耦合强度、层数的增大会使同步能力增强,层内耦合强度、层间叶子节点之间的耦合强度的增大反而会使同步能力减弱.对于中心节点向叶子节点耦合的多层星形网络,层间叶子节点之间的耦合强度、层数的增大会使同步能力增强,层内耦合强度、节点数、层间中心节点之间的耦合强度的增大反而会使同步能力减弱.     

Self-sustained oscillations of complex genomic regulatory networks

Recently, self-sustained oscillations in complex networks consisting of non-oscillatory nodes have attracted great interest in diverse natural and social fields. Oscillatory genomic regulatory networks are one of the most typical examples of this kind. Given an oscillatory genomic network, it is important to reveal the central structure generating the oscillation. However, if the network consists of large numbers of genes and interactions, the oscillation generator is deeply hidden in the complicated interactions. We apply the dominant phase-advanced driving path method proposed in Qian et al. (2010) [1] to reduce complex genomic regulatory networks to one-dimensional and unidirectionally linked network graphs where negative regulatory loops are explored to play as the central generators of the oscillations, and oscillation propagation pathways in the complex networks are clearly shown by tree branches radiating from the loops. Based on the above understanding we can control oscillations of genomic networks with high efficiency.     

Designer gene networks: Towards fundamental cellular control

The engineered control of cellular function through the design of synthetic genetic networks is becoming plausible. Here we show how a naturally occurring network can be used as a parts list for artificial network design, and how model formulation leads to computational and analytical approaches relevant to nonlinear dynamics and statistical physics. We first review the relevant work on synthetic gene networks, highlighting the important experimental findings with regard to genetic switches and oscillators. We then present the derivation of a deterministic model describing the temporal evolution of the concentration of protein in a single-gene network. Bistability in the steady-state protein concentration arises naturally as a consequence of autoregulatory feedback, and we focus on the hysteretic properties of the protein concentration as a function of the degradation rate. We then formulate the effect of an external noise source which interacts with the protein degradation rate. We demonstrate the utility of such a formulation by constructing a protein switch, whereby external noise pulses are used to switch the protein concentration between two values. Following the lead of earlier work, we show how the addition of a second network component can be used to construct a relaxation oscillator, whereby the system is driven around the hysteresis loop. We highlight the frequency dependence on the tunable parameter values, and discuss design plausibility. We emphasize how the model equations can be used to develop design criteria for robust oscillations, and illustrate this point with parameter plots illuminating the oscillatory regions for given parameter values. We then turn to the utilization of an intrinsic cellular process as a means of controlling the oscillations. We consider a network design which exhibits self-sustained oscillations, and discuss the driving of the oscillator in the context of synchronization. Then, as a second design, we consider a synthetic network with parameter values near, but outside, the oscillatory boundary. In this case, we show how resonance can lead to the induction of oscillations and amplification of a cellular signal. Finally, we construct a toggle switch from positive regulatory elements, and compare the switching properties for this network with those of a network constructed using negative regulation. Our results demonstrate the utility of model analysis in the construction of synthetic gene regulatory networks. (c) 2001 American Institute of Physics.     

基于感知流量算法的复杂网络拥塞问题研究

研究了在具有感知流量的路由策略下,复杂网络的拓扑结构对网络中传输流量的影响.为了描述数据包传输过程的有效性,通过引入一个状态参数,利用由稳态到拥塞的指标流量相变值来刻画网络的吞吐量.基于每个节点的数据包处理能力与该节点的度或介数成比例提出两种模型并进行仿真.仿真结果表明,平均度相同的情况下,模型Ⅰ中,WS小世界网络比ER随机网络和BA无标度网络更容易产生拥塞;模型Ⅱ中,所有网络容量都得到较大的提高,尤其是WS小世界网络.但当网络的基本连接参数改变时,哪种模型更利于网络的流量传输,还要依据网络本身的结构特性 关键词： 复杂网络 无标度网络 感知流量 拥塞     

Blocking probability analysis model for flexible spectrum optical networks

Compared to the traditional wavelength division multiplexing （WDM） optical networks with rigid and coarse granularities, flexible spectrum optical networks have high spectrum efficiency, which can support the service with various bandwidth requirements, such as sub and super channel. Among all network performance parameters, blocking probability is an important parameter for the performance evaluation and network planning in circuit~based optical networks including flexible spectrum optical networks. We propose an analytical method of blocking probability computation for flexible spectrum optical networks in this letter through mathematical analysis and theoretical derivation. Two blocking probability models are built respectively based on whether considering spectrum consecutiveness or not. Numerical results validate our proposed blocking probability models under different link capacity and traffic loads.     

Adaptive bridge control strategy for opinion evolution on social networks

In this paper, we present an efficient opinion control strategy for complex networks, in particular, for social networks. The proposed adaptive bridge control (ABC) strategy calls for controlling a special kind of nodes named bridge and requires no knowledge of the node degrees or any other global or local knowledge, which are necessary for some other immunization strategies including targeted immunization and acquaintance immunization. We study the efficiency of the proposed ABC strategy on random networks, small-world networks, scale-free networks, and the random networks adjusted by the edge exchanging method. Our results show that the proposed ABC strategy is efficient for all of these four kinds of networks. Through an adjusting clustering coefficient by the edge exchanging method, it is found out that the efficiency of our ABC strategy is closely related with the clustering coefficient. The main contributions of this paper can be listed as follows: (1) A new high-order social network is proposed to describe opinion dynamic. (2) An algorithm, which does not require the knowledge of the nodes' degree and other global∕local network structure information, is proposed to control the "bridges" more accurately and further control the opinion dynamics of the social networks. The efficiency of our ABC strategy is illustrated by numerical examples. (3) The numerical results indicate that our ABC strategy is more efficient for networks with higher clustering coefficient.     

Proposal of Rip up & Re allocate Algorithm for Optical Layer 2 Switch Network

We are developing an optical layer-2s witch network that uses both wavelength-division multiplexing and time-division multiplexing technologies for efficient traffic aggregation in metro networks.For efficient traffic aggregation,path bandwidth control is key because it strongly affects bandwidth efficiency.For this paper,we propose a dynamic time-slot allocation method that uses periodic information of difference values of traffic variation.This method can derive near-optimal allocation with lower computational cost,which enlarges the maximum available network size compared with conventional time-slot allocation methods.Numerical results show that the proposed method enables dynamic path control in 1K-node-scale optical layer-2s witch network,which leads to cost-effective metro networks.     

Complex networks: Dynamics and security

This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. In particular, we review two related problems: attack-induced cascading breakdown and range-based attacks on links. A cascade in a network means the failure of a substantial fraction of the entire network in a cascading manner, which can be induced by the failure of or attacks on only a few nodes. These have been reported for the internet and for the power grid (e.g., the August 10, 1996 failure of the western United States power grid). We study a mechanism for cascades in complex networks by constructing a model incorporating the flows of information and physical quantities in the network. Using this model we can also show that the cascading phenomenon can be understood as a phase transition in terms of the key parameter characterizing the node capacity. For a parameter value below the phase-transition point, cascading failures can cause the network to disintegrate almost entirely. We will show how to obtain a theoretical estimate for the phase-transition point. The second problem is motivated by the fact that most existing works on the security of complex networks consider attacks on nodes rather than on links. We address attacks on links. Our investigation leads to the finding that many scale-free networks are more sensitive to attacks on short-range than on long-range links. Considering that the small-world phenomenon in complex networks has been identified as being due to the presence of long-range links, i.e., links connecting nodes that would otherwise be separated by a long node-to-node distance, our result, besides its importance concerning network efficiency and security, has the striking implication that the small-world property of scale-free networks is mainly due to short-range links.     

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

We develop an online adaptive dynamic programming （ADP） based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.     

An estimation formula for the average path length of scale-free networks

A universal estimation formula for the average path length of scale free networks is given in this paper. Different from other estimation formulas, most of which use the size of network, $N$, as the only parameter, two parameters including $N$ and a second parameter $\alpha $ are included in our formula. The parameter $\alpha $ is the power-law exponent, which represents the local connectivity property of a network. Because of this, the formula captures an important property that the local connectivity property at a microscopic level can determine the global connectivity of the whole network. The use of this new parameter distinguishes this approach from the other estimation formulas, and makes it a universal estimation formula, which can be applied to all types of scale-free networks. The conclusion is made that the small world feature is a derivative feature of a scale free network. If a network follows the power-law degree distribution, it must be a small world network. The power-law degree distribution property, while making the network economical, preserves the efficiency through this small world property when the network is scaled up. In other words, a real scale-free network is scaled at a relatively small cost and a relatively high efficiency, and that is the desirable result of self-organization optimization.