Comparison of immunization strategies in geographical networks

The epidemic spread and immunizations in geographically embedded scale-free (SF) and Watts-Strogatz (WS) networks are numerically investigated. We make a realistic assumption that it takes time which we call the detection time, for a vertex to be identified as infected, and implement two different immunization strategies: one is based on connection neighbors (CN) of the infected vertex with the exact information of the network structure utilized and the other is based on spatial neighbors (SN) with only geographical distances taken into account. We find that the decrease of the detection time is crucial for a successful immunization in general. Simulation results show that for both SF networks and WS networks, the SN strategy always performs better than the CN strategy, especially for more heterogeneous SF networks at long detection time. The observation is verified by checking the number of the infected nodes being immunized. We found that in geographical space, the distance preferences in the network construction process and the geographically decaying infection rate are key factors that make the SN immunization strategy outperforms the CN strategy. It indicates that even in the absence of the full knowledge of network connectivity we can still stop the epidemic spread efficiently only by using geographical information as in the SN strategy, which may have potential applications for preventing the real epidemic spread.     

复杂网络的顶点着色及其在疾病免疫中的应用

在复杂网络研究中, 对于网络结构特征的分析已经引起了人们的极大关注, 而其中的网络着色问题却没有得到足够的重视. 为了理解网络结构与着色之间的关系, 本文研究了WS, BA网络以及不同宏观结构参量对于正常K色数的影响, 发现最大团数可以大致反映正常K色数的变化趋势, 而网络的平均度和匹配系数比异质性和聚类系数对于色数的影响更大. 对于一些实际网络的正常着色验证了本文的分析结果. 对复杂网络的顶点进行着色后, 根据独立集内任意两个顶点均不相邻的特点, 我们提出了基于独立集的免疫策略. 与全网随机免疫相比, 基于独立集的免疫策略可令网络更为脆弱, 从而有效抑制疾病的传播. 基于网络着色的独立集提供了一种崭新的免疫思路, 作为一个简单而适用的平台,有助于设计更为有效的免疫策略. 关键词： 复杂网络 正常着色 独立集 免疫策略     

Gallium arsenide optoelectronic IC's for computer networks

The physics of gallium arsenide offers distinct advantages compared to silicon for device applications based on mobility, epitaxial bandgap engineering, and optoelectronic function. Because of these advantages, compared to silicon, gallium arsenide transistors and optoelectronic devices are likely to be found in future computer systems. I first discuss material advantages and challenges for commercial realization of these applications. Examples of these potential applications in communication and computer systems are given. Highly integrated optoelectronic circuits will likely be found in optical links for data communications. The state of the art will be illustrated with recent results from a joint program that spans several IBM research and development laboratories. A demonstration of a compactly packaged gigabit per second optical data link with error rates low enough for computer communications has been made with two highly integrated MESFET chips and one laser array.     

Epidemic threshold and immunization on generalized networks

The susceptible–infected–susceptible (SIS) model is widely adopted in the studies of epidemic dynamics. When it is applied on contact networks, these networks mostly consist of nodes connected by undirected and unweighted edges following certain statistical properties, whereas in this article we consider the threshold and immunization problem for the SIS model on generalized networks that may contain different kinds of nodes and edges which are very possible in the real situation. We proved that an epidemic will become extinct if and only if the spectral radius of the corresponding parameterized adjacent matrix (PAM) is smaller than 1. Based on this result, we can evaluate the efficiency of immune strategies and take several prevailing ones as examples. In addition, we also develop methods that can precisely find the optimal immune strategies for networks with the given PAM.     

Imperfect targeted immunization in scale-free networks

Scale-free networks are prone to epidemic spreading. To provide cost-effective protection for such networks, targeted immunization was proposed to selectively immunize the hub nodes. In many real-life applications, however, the targeted immunization may not be perfect, either because some hub nodes are hidden and consequently not immunized, or because the vaccination simply cannot provide perfect protection. We investigate the effects of imperfect targeted immunization in scale-free networks. Analysis and simulation results show that there exists a linear relationship between the inverse of the epidemic threshold and the effectiveness of targeted immunization. Therefore, the probability of epidemic outbreak cannot be significantly lowered unless the protection is reasonably strong. On the other hand, even a relatively weak protection over the hub nodes significantly decreases the number of network nodes ever getting infected and therefore enhances network robustness against virus. We show that the above conclusions remain valid where there exists a negative correlation between nodal degree and infectiousness.     

Effective vaccination strategies for realistic social networks

We consider the effectiveness of targeted vaccination at preventing the spread of infectious disease in a realistic social network. We compare vaccination strategies based on no information (random vaccination) to complete information (PageRank) about the network. The most effective strategy we find is to vaccinate those people with the most unvaccinated contacts. However, this strategy requires considerable information and computational effort which may not be practical. The next best strategies vaccinate people with many contacts who in turn have few contacts.     

Dynamics of simple computer networks

We consider a simple two-dimensional layered automaton. Each processor in the automaton performs the same nonlinear, thresholdlike operation (so that the row-to-row evolution of the array can also be seen as the time development of a one-dimensional automaton). One row of the machine is reserved for input, another is singled out as output. We study the output space in detail, as restricted by the very wiring of the array, enumerating the output configurations, and characterizing them statistically. We demonstrate that input configurations flow to a set of zero measure in output space. The variations in output that are to be expected when input is subjected to perturbations are also examined.     

Efficient modal control strategies for active control of vibrations

Some efficient strategies for the active control of vibrations of a beam structure using piezoelectric materials are described. The control algorithms have been implemented for a cantilever beam model developed using finite element formulation. The vibration response of the beam to an impulse excitation has been calculated numerically for the uncontrolled and the controlled cases. The essence of the method proposed is that a feedback force in different modes be applied according to the vibration amplitude in the respective modes i.e., modes having lesser vibration may receive lesser feedback. This weighting may be done on the basis of either displacement or energy present in different modes. This method is compared with existing methods of modal space control, namely the independent modal space control (IMSC), and modified independent modal space control (MIMSC). The method is in fact an extension of the modified independent space control with the addition that it proposes to use the sum of weighted multiple modal forces for control. The proposed method results in a simpler feedback, which is easy to implement on a controller. The procedure is illustrated for vibration control of a cantilever beam. The analytical results show that the maximum feedback control voltage required in the proposed method is further reduced as compared to existing methods of IMSC and MIMSC for similar vibration control. The limitations of the proposed method are discussed.     

Delayed commutation in quantum computer networks

In the same way that classical computer networks connect and enhance the capabilities of classical computers, quantum networks can combine the advantages of quantum information and communication. We propose a nonclassical network element, a delayed commutation switch, that can solve the problem of switching time in packet switching networks. With the help of some local ancillary qubits and superdense codes, we can route a qubit packet after part of it has left the network node.     

Efficient and robust routing on scale-free networks

Information routing is one of the most important problems in large communication networks. In this paper we propose a novel routing strategy in which the optimal paths between all pairs of nodes are chosen according to a cost function that incorporates degrees of nodes in paths. Results on large scale-free networks demonstrate that our routing strategy is more efficient than the shortest path algorithm and the efficient routing strategy proposed by Yan et al. [Phys. Rev. E 73, 046108 (2006)]. Furthermore our routing strategy has strong robustness against cascading failure attacks on networks.     

考虑网络流量的无标度网络病毒免疫策略研究

考虑网络交通流量对病毒传播行为的影响,基于平均场理论研究无标度网络上的病毒免疫策略,提出一种改进的熟人免疫机理.理论分析表明,在考虑网络交通流量影响的情况下,当免疫节点密度较小时,随机免疫几乎不能降低病毒的传播速率,而对网络实施目标免疫则能够有效抑制病毒的传播,并且选择度最大的节点进行免疫与选择介数最大的节点进行免疫的效果基本相同.研究还发现,对于网络全局信息未知的情况,与经典熟人免疫策略相比,所提出的免疫策略能够获得更好的免疫效果.通过数值仿真对理论分析进行了验证. 关键词： 无标度网络 病毒传播 交通流量 免疫策略     

基于传播免疫的复杂网络可控性研究

复杂网络控制反映了人类对复杂系统的认识深度和改造能力. 最新研究成果基于线性系统控制理论建立了复杂网络可控性的理论架构, 能够发现任意拓扑结构的线性时不变复杂网络中控制全部节点状态的最小驱动节点集, 但是该模型未考虑免疫节点或失效节点对控制信号传播的阻断.在继承该模型优点的前提下, 重新构建了基于传播免疫的复杂网络控制模型.在采用分属于随机免疫和目标免疫两种策略的 4个方法确定免疫节点的情况下,分析14个真实网络的可控性.结果表明:如果将网络中度数、 介数和紧密度指标较高的节点作为免疫节点,将极大地提高控制复杂网络的难度. 从而在一定程度上丰富了以往模型的结论.     

复杂网络中考虑不完全免疫的病毒传播研究

复杂网络中不完全免疫包括免疫失败和免疫失效两种情况,本文研究两者同时存在对网络病毒传播行为的影响,基于平均场理论,提出一种新的传播模型.理论分析表明,免疫失败和免疫失效同时存在显著降低了网络的传播临界值,增强了病毒的感染程度.根据传播临界值与免疫节点密度、免疫成功率以及免疫失效率之间的关系,给出有效控制网络病毒传播的策略.通过数值仿真进行验证。     

Efficient promotion strategies in hierarchical organizations

The Peter principle has recently been investigated by means of an agent-based simulation, and its validity has been numerically corroborated. It has been confirmed that, within certain conditions, it can really influence in a negative way the efficiency of a pyramidal organization adopting meritocratic promotions. It was also found that, in order to bypass these effects, alternative promotion strategies should be adopted, as for example a random selection choice. In this paper, within the same line of research, we study promotion strategies in a more realistic hierarchical and modular organization, and we show the robustness of our previous results, extending their validity to a more general context. We also discuss why the adoption of these strategies could be useful for real organizations.     

Efficient temperature compensation strategies for guided wave structural health monitoring

The application of temperature compensation strategies is important when using a guided wave structural health monitoring system. It has been shown by different authors that the influence of changing environmental and operational conditions, especially temperature, limits performance. This paper quantitatively describes two different methods to compensate for the temperature effect, namely optimal baseline selection (OBS) and baseline signal stretch (BSS). The effect of temperature separation between baseline time-traces in OBS and the parameters used in the BSS method are investigated. A combined strategy that uses both OBS and BSS is considered. Theoretical results are compared, using data from two independent long-term experiments, which use predominantly A₀ mode and S₀ mode data respectively. These confirm that the performance of OBS and BSS quantitatively agrees with predictions and also demonstrate that the combination of OBS and BSS is a robust practical solution to temperature compensation.     

Efficient label distribution mechanism for bidirectional paths in MPLS-TP networks

Transport network paths are typically bidirectional and symmetrical. In multi-protocol label switching (MPLS) and generalized MPLS (GMPLS) mechanisms, independent labels are distributed for bidirectional paths. Thus, the requirement of the MPLS transport profile (MPLS-TP), which is a new transport technology, could not be satisfied efficiently. A novel label distribution mechanism for bidirectional paths in MPLS-TP networks is proposed. Labels distributed by the mechanism are symmetrical and can re?ect the pairing relationship of the forward and backward directions of the transport path.     

Culture and evolution on populations of neural networks

Although acquired characteristics are not incorporated into the genotype, some works have pointed to the influence of learning in evolution. We present a dynamic model of neural networks presenting evolutive features, even without modification in genotype, due to the introduction of culture. Our model presents other features that seem to reproduce some aspects of real world populations.     

多层网络级联失效的预防和恢复策略概述

现实生活中,与国计民生密切相关的基础设施网络大多不是独立存在的,而是彼此之间相互联系或依赖的,于是用于研究这些系统的多层网络模型随之产生.多层网络中的节点在失效或者遭受攻击后会因"层内"和"层间"的相互作用而产生级联效应,从而使得失效能够在网络层内和层间反复传播并使得失效规模逐步放大.因此,多层网络比单个网络更加脆弱.多层网络级联失效产生的影响和损失往往是非常巨大的,所以对多层网络级联失效的预防和恢复的研究具有重大意义.就多层网络级联失效的预防而言,主要包含故障检测,保护重要节点,改变网络耦合机制和节点备份等策略.就多层网络发生级联失效后的恢复策略而言,主要包含共同边界节点恢复、空闲连边恢复、加边恢复、重要节点优先恢复、更改拓扑结构、局域攻击修复、自适应边修复等策略.     

Efficient packet routing strategy in complex networks

We investigate a new efficient packet routing strategy which mitigates traffic congestion on complex networks. In order to avoid congestion, we minimize the maximum betweenness, which is a measure for concentration of routing paths passing through a node in the network. Danila et al. propose a packet routing strategy in which, instead of shortest paths, they used efficient paths, which are the paths with the minimum total summations of weights assigned to nodes in the respective paths. They use a heuristic algorithm in which the weights are updated step by step by using the information of betweenness of each node in every step and the respective total summations of weights for paths through the nodes with large degrees become comparatively large. Thus passage through such nodes, where congestion almost occurs, is likely to be avoided in their algorithm. The convergence time by their algorithm is, however, quite long. In this paper, we propose a new efficient heuristic algorithm which balances traffic on networks by achieving minimization of the maximum betweenness in the much smaller number of iteration steps for convergence than that by the algorithm of Danila et al.     

Effect of attachment strategies on bipartite networks

Bipartite systems show remarkable variations in their topological asymptotic properties,e.g., in their degree distribution. Such variations depend on the underlying growthdynamics. A scenario of particular importance is when the two partitions of the bipartitestructure do not grow at an equal rate. Here, we focus on the case where one of thepartitions can be assumed to be fixed while the other partition grows in time as observedin the codon-gene or alphabet-word network. We show that subtle changes in growthdynamics, particularly in the attachment kernel, can lead to drastic changes of theemergent topological properties. We present a detail analysis of various growthstrategies, including sequential and parallel addition of nodes, as well as with andwithout replacement attachment kernels. Analytical results have been compared withstochastic simulations as well as with real systems showing in all cases an excellentagreement.