共查询到18条相似文献,搜索用时 187 毫秒
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计算机网络病毒传播模型SIRH 总被引:1,自引:0,他引:1
计算机网络病毒传播模型是研究计算机网络病毒的手段和工具。SIR模型是仿照生物流行病传播机制而建立的病毒传播模型。本文从计算机网络病毒传播的实际情况出发,通过分析SIR模型的不足,提出了一种在计算机网络中具有病毒防范、病毒免疫措施的网络病毒传播模型。SIRH考虑了网络病毒重复感染这种人为因素对网络病毒传播的影响。仿真实验验证了SIRH的有效合理性。 相似文献
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一种计算机网络病毒传播数学模型 总被引:5,自引:0,他引:5
研究计算机病毒在网络上进行传播的数学模型,可以深刻理解病毒扩散对网络造成危害的现象,为反病毒技术研究提供理论基础.本文通过在典型网络环境下病毒传播数学模型的建立和分析,得出了遏制网络病毒迅速扩散的重要环节和策略. 相似文献
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为了研究免疫有效时间对复杂网络中病毒传播的影响,基于元胞自动机建立复杂网络不完全免疫的病毒传播模型,并分别在最近邻耦合网络、Erdos-Renyi随机网络、Watts-Strogatz小世界网络和Barabasi-Albert无标度网络中进行仿真研究。结果表明:节点免疫有效时间的增大,能够有效地遏制复杂网络病毒传播范围并增大病毒传播阈值。 相似文献
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为有效地模拟病毒在适应网络中的传播,分析了当前适应网络病毒传播研究的现状,结合适应网络中存在的节点动力学和网络动力学相互作用、相互反馈的机制,提出了一种基于计算机仿真技术的适应网络病毒传播的SIS(susceptibleinfected-susceptible)离散模型.通过对所建模型进行仿真和分析,实验结果表明,病毒在适应网络中传播具有双稳态性;由于节点规避病毒传播而改变网络连接的行为,使得网络的度分布发生变化,该行为对病毒在网络中的传播具有抑制作用. 相似文献
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病毒传播过程中个体的躲避行为对网络结构的影响* 总被引:2,自引:2,他引:0
为了研究病毒传播过程中个体的运动行为对网络结构的影响,提出了一种个体具有躲避行为的病毒传播模型,通过三种情况下的对比研究发现,个体的躲避行为能够使网络的结构从随机网络转换为一种宽标度网络,并且发现系统在演化过程中个体的躲避行为能够使网络的度—度相关性发生变化,这证实了个体的躲避行为确实对会网络结构产生影响。 相似文献
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自适应网络病毒传播重点研究节点传播动力学和网络动力学之间的相互作用和反馈.考虑到病毒在网络中传播存在时延,文中使用异步元胞自动机和健康节点规避病毒传播的断边重连行为建立一种具有传播时延的自适应网络病毒传播模型.对所建模型的仿真结果表明,重连行为和传播时延的联合作用使节点状态演化不同步进行,病毒的传播速率变缓,爆发规模降低.这种基于异步元胞自动机建立的传播模型很好表达了自适应网络中的网络传播时延,病毒传播和网络结构演化的相互作用和反馈. 相似文献
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病毒传播问题的研究一直是国际上科学家所关注的焦点,但是在加权局域网络中的病毒传播研究却是空白。由于实际存在的网络很大一部分是加权局域网络,因此研究了一种特定加权局域网络中的传播行为。采用病毒传播的SI模型,令病毒的传播速度和网络的连接权重正相关。对加权局域网络中病毒传播行为的研究表明:加权局域网络的无标度性质和加权局域世界性质对病毒的传播有深刻的影响。由于加权局域网络能够很好地反应实际世界,因此该研究具有很广的应用背景。 相似文献
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Chengyi XIA Shiwen SUN Feng RAO Junqing SUN Jinsong WANG Zengqiang CHEN 《Frontiers of Computer Science》2009,3(3):361
We present a new epidemic Susceptible-Infected-Susceptible (SIS) model to investigate the spreading behavior on networks with dynamical topology and community structure. Individuals in themodel are mobile agentswho are allowed to perform the inter-community (i.e., long-range) motion with the probability p. The mean-field theory is utilized to derive the critical threshold (λC) of epidemic spreading inside separate communities and the influence of the long-range motion on the epidemic spreading. The results indicate that λC is only related with the population density within the community, and the long-range motion will make the original disease-free community become the endemic state. Large-scale numerical simulations also demonstrate the theoretical approximations based on our new epidemic model. The current model and analysis will help us to further understand the propagation behavior of real epidemics taking place on social networks. 相似文献
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Chengyi Xia Shiwen Sun Feng Rao Junqing Sun Jinsong Wang Zengqiang Chen 《Frontiers of Computer Science in China》2009,3(3):361-365
We present a new epidemic Susceptible-Infected-Susceptible (SIS) model to investigate the spreading behavior on networks with
dynamical topology and community structure. Individuals in themodel are mobile agentswho are allowed to perform the inter-community
(i.e., long-range) motion with the probability p. The mean-field theory is utilized to derive the critical threshold (λ
C
) of epidemic spreading inside separate communities and the influence of the long-range motion on the epidemic spreading.
The results indicate that λ
C
is only related with the population density within the community, and the long-range motion will make the original disease-free
community become the endemic state. Large-scale numerical simulations also demonstrate the theoretical approximations based
on our new epidemic model. The current model and analysis will help us to further understand the propagation behavior of real
epidemics taking place on social networks. 相似文献
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Based on the mean-field approach, epidemic spreading has been well studied. However, the mean-field approach cannot show the
detailed contagion process, which is important in the control of epidemic. To fill this gap, we present a novel approach to
study how the topological structure of complex network influences the concrete process of epidemic spreading. After transforming
the network structure into hierarchical layers, we introduce a set of new parameters, i.e., the average fractions of degree
for outgoing, ingoing, and remaining in the same layer, to describe the infection process. We find that this set of parameters
are closely related to the degree distribution and the clustering coefficient but are more convenient than them in describing
the process of epidemic spreading. Moreover, we find that the networks with exponential distribution have slower spreading
speed than the networks with power-law degree distribution. Numerical simulations have confirmed the theoretical predictions. 相似文献
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Based on the mean-field approach, epidemic spreading has been well studied. However, the mean-field approach cannot show the detailed contagion process, which is important in the control of epidemic. To fill this gap, we present a novel approach to study how the topological structure of complex network influences the concrete process of epidemic spreading. After transforming the network structure into hierarchical layers, we introduce a set of new parameters, i.e., the average fractions of degree for outgoing, ingoing, and remaining in the same layer, to describe the infection process. We find that this set of parameters are closely related to the degree distribution and the clustering coefficient but are more convenient than them in describing the process of epidemic spreading. Moreover, we find that the networks with exponential distribution have slower spreading speed than the networks with power-law degree distribution. Numerical simulations have confirmed the theoretical predictions. 相似文献
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刘天印 《计算机工程与应用》2011,47(15):222-224
研究2009年我国A(H1N1)型流感大流行的病毒传播规律以及预防控制策略,发展复杂网络上的传播动力学理论,以提高应对类似甲流的、突发的世界公共卫生危机的能力。建立基于复杂网络的小世界效应和无标度特性的SIRD病毒传播模型,采用中国疾病预防控制中心的甲流传播数据,选择AnyLogic仿真平台对一个中等规模城市的甲流传播进行仿真实验。仿真数据表明:学校停课、限制人口自由流动、扩大疑似病例的处理范围、接种疫苗等是控制疫情大爆发的有效措施,并存在控制强度的临界值。 相似文献
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In this paper, we investigate the problem of designing event-triggered controllers for containing epidemic processes in complex networks. We focus on a deterministic susceptible–infected–susceptible (SIS) model, which is one of the well-known, fundamental models that capture the epidemic spreading. The event-triggered control is particularly formulated in the context of viral spreading, in which control inputs (e.g., the amount of medical treatments, a level of traffic regulations) for each subpopulation are updated only when the fraction of the infected people in the subpopulation exceeds a prescribed threshold. We analyze the stability of the proposed event-triggered controller and derive a sufficient condition for a prescribed control objective to be achieved. Moreover, we propose a novel emulation-based approach towards the design of the event-triggered controller, and show that the problem of designing the event-triggered controller can be solved in polynomial time using a geometric programming. We illustrate the effectiveness of the proposed approach through numerical simulations using an air transportation network. 相似文献
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