动态演化的互联网病毒建模与分析

互联网是一个不断生长的无标度网络,在其生长过程中伴随着计算机病毒的传播。基于此,兼顾静态和动态网络上的病毒传播过程,建立了含有拓扑结构演化的计算机病毒传播模型,研究了网络增长速度、网络平均度以及计算机连接度对病毒传播的影响。实验结果表明,网络演化速度越快,病毒传播也越快。同时平均度较高的网络更有助于病毒的传播。此外,病毒在爆发期间主要集中在连接度较大的计算机上。所得结论对控制病毒传播意义重大。     

病毒在无标度网络上的传播及控制仿真研究*

网络病毒的爆发给计算机用户带来巨大的损失,同时互联网被认为是无标度网络,因此研究病毒在无标度网络上的传播及控制很有意义。通过构建一个BA无标度网络模型,对病毒的传播行为及影响因素进行了仿真分析。研究表明,采取恰当的策略可以有效地控制、预防病毒传播。     

电子邮件病毒传播的元胞自动机建模与分析*

为研究电子邮件病毒在有向无标度网络上的传播行为,基于元胞自动机理论,提出一个电子邮件病毒传播的元胞自动机模型。在该模型下,仿真分析多种因素对电子邮件病毒传播行为的影响,结果表明：在给定的有向无标度网络中,病毒传播速度和传播规模随着电子邮件病毒附件打开概率增加而增大,网络的有向性增加病毒传播规模对于免疫概率的敏感性,病毒传播演化主要与节点入度相关。研究还表明,病毒先感染入度大的节点,后感染入度小的节点,而节点感染病毒先后顺序与节点出度没有明显关系。     

二部无标度网络上病毒传播模型和免疫策略研究

针对计算机网络上的病毒传播问题,提出一种二部无标度网络,其节点分为客户机和服务器两类。在二部无标度网络上应用易感-感染-易感(SIS)传播模型,采用率方程的方法研究二部无标度网络上病毒的状态转移和临界行为,得出客户机感染密度与服务器感染密度的关系式。在SIS模型的基础上利用免疫策略,针对相同的网络拓扑和病毒传播模型,分析比较免疫策略的免疫功能,并给出支持理论结果的数值模拟,结果验证了随机免疫、节点度免疫与相识点免疫策略都具有防御病毒传播的功能,并且防疫能力依次增强。     

基于异质移动网络的破坏性病毒传播模型

针对现有研究没有考虑移动网络节点异质性与没有构建破坏性病毒传播模型的问题,提出一个基于异质移动网络的破坏性病毒传播模型。通过考虑移动网络节点的异质性,进一步将易感染状态划分为新系统状态和旧系统状态,并结合破坏性病毒的潜伏与爆发特性将感染状态划分为潜伏状态和爆发状态。计算了模型的平衡点与传播阈值,并指出当传播阈值大于1时,模型在正平衡点处不稳定;当传播阈值小于1时,模型在正平衡点处局部渐近稳定。在NW小世界网络和BA无标度网络上进行仿真对比实验,仿真结果表明,两个网络的病毒传播速度不同,NW网络存在病毒完全消除的情况,而BA网络中的病毒不会被完全清除。     

基于元胞自动机的自适应网络断边重连策略研究*

为了有效控制自适应复杂网络中病毒的传播,本文对自适应网络的重连策略进行了系统的研究。基于先前研究中网络断边后,随机地或根据节点度、欧几里德距离进行重连的策略,提出了基于最短路径和节点度的重连策略。首先根据元胞自动机理论建立自适应复杂网络的病毒传播模型。在此基础上,分别在WS小世界网络和BA无标度网络中对Random-RE策略、Degree-RE策略、SP-RE策略、SP-Degree-RE策略和Degree-SP-RE策略进行比较分析。实验结果表明, SP-Degree策略能够有效破坏具有小世界特征网络的传输性和连通性,对其抑制病毒传播效果最好;而Degree-SP策略能够有效破坏无标度特征网络的传输性和连通性,对其抑制病毒传播效果最好。     

微博病毒传播模型研究

利用有向无标度网络描述微博用户的关系,在此基础上建立微博病毒传播模型,研究用户点击率、转发率以及对信息的反应速度等因素对病毒传播的影响。实验结果表明,用户点击恶意链接的行为能促使病毒传播,转发警告信息的行为能抑制病毒扩散,对信息做出反应经历的时间越短,病毒及警告信息传播得越快,并且越早对病毒采取抵制措施,病毒爆发的范围越小。     

适应网络病毒传播的SIS离散模型

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.     

多局域世界复杂网络中的病毒传播研究

对多局域世界(MLW)演化模型的构造算法进行改进,以元胞自动机(CA)为工具,研究MLW复杂网络中的病毒传播特性。结果表明,CA能较好反映病毒传播过程中的概率事件和个体之间的交互行为,MLW复杂网络的传播临界值与传染率、病毒爆发率有关,初始感染源的选择对病毒的爆发有重要作用,病毒的传播和消亡速度与传染率以及攻击模式有关。     

移动自组网病毒传播模型及稳定性分析

考虑移动自组网中节点的移动特性,基于平均场理论提出移动自组网中病毒传播模型,并对建立的方程组进行平衡点存在性和稳定性分析,得出病毒传播的阈值及消亡条件,从而研究节点移动速度、通信半径、免疫成功率和免疫失效率对移动自组网中病毒传播行为和传播临界特性的影响。结果表明:当病毒基本再生数R0<1时,网络全局渐近稳定在无病毒平衡点;当R0>1时,网络全局渐近稳定在地方病平衡点。最后通过数值仿真验证了该模型的正确性。     

Rethinking the architecture design of data center networks

In the rising tide of the Internet of things, more and more things in the world are connected to the Internet. Recently, data have kept growing at a rate more than four times of that expected in Moore’s law. This explosion of data comes from various sources such as mobile phones, video cameras and sensor networks, which often present multidimensional characteristics. The huge amount of data brings many challenges on the management, transportation, and processing IT infrastructures. To address these challenges, the state-of-art large scale data center networks have begun to provide cloud services that are increasingly prevalent. However, how to build a good data center remains an open challenge. Concurrently, the architecture design, which significantly affects the total performance, is of great research interest. This paper surveys advances in data center network design. In this paper we first introduce the upcoming trends in the data center industry. Then we review some popular design principles for today’s data center network architectures. In the third part, we present some up-to-date data center frameworks and make a comprehensive comparison of them. During the comparison, we observe that there is no so-called optimal data center and the design should be different referring to the data placement, replication, processing, and query processing. After that, several existing challenges and limitations are discussed. According to these observations, we point out some possible future research directions.     

Currents in connectionism

This paper reviews four significant advances on the feedforward architecture that has dominated discussions of connectionism. The first involves introducing modularity into networks by employing procedures whereby different networks learn to perform different components of a task, and a Gating Network determines which network is best equiped to respond to a given input. The second consists in the use of recurrent inputs whereby information from a previous cycle of processing is made available on later cycles. The third development involves developing compressed representations of strings in which there is no longer an explicit encoding of the components but where information about the structure of the original string can be recovered and so is present functionally. The final advance entails using connectionist learning procedures not just to change weights in networks but to change the patterns used as inputs to the network. These advances significantly increase the usefulness of connectionist networks for modeling human cognitive performance by, among other things, providing tools for explaining the productivity and systematicity of some mental activities, and developing representations that are sensitive to the content they are to represent.A version of this paper was the invited address at the first annual conference of the Society for Machines and Mentality in December, 1991. A related version was presented at the Computers and Philosophy Conference in August, 1992. I am extremely grateful to Adele Abrahamsen for her numerous suggestions and comments on various drafts of this paper.     

复杂网络聚类算法在生物网络中的应用

复杂网络在现实世界中普遍存在,具有小世界性和无标度性等统计特性,网络簇结构是复杂网络重要的拓扑属性之一。在复杂生物网络中使用聚类算法揭示生物网络中的簇结构对分析生物网络的拓扑结构、预测其功能都具有重要意义。对复杂网络聚类方法在蛋白质-蛋白质相互作用网络和新陈代谢网络中的应用及其进展情况进行了综述,分析了几种聚类算法的评价函数和适用条件,并对生物网络聚类算法研究所面临的主要问题进行了讨论。     

因子分解二终端网络可靠度近似计算

因子分解算法可以用来计算网络可靠度精确值,但对于大型网络,可靠度精确值的计算非常困难。基于时间和精确度的双重考虑,在精确算法的基础上通过改进得出一种近似算法。实验结果证明,该算法得到的近似值接近精确值,而且计算时间要低于精确算法。     

A middleware for industry

This paper describes an innovative distributed framework for monitoring and control of large-scale systems by integrating heterogeneous smart objects, the world of physical devices, sensors and actuators, legacy devices and sub-systems, cooperating to support holistic management [1]. Its featured Service Oriented Architecture (SOA) exposes objects’ capabilities by means of web services, thus supporting syntactic and semantic interoperability among different technologies, including SCADA systems [23]. Wireless Sensor and Actuator Network (WSAN) devices and legacy subsystems cooperate while orchestrated by a manager in charge of enforcing a distributed logic. Particularly crafted for industrial networks are new middleware services such as dynamic spectrum management, distributed control logic, object virtualization, WSANs gateways, a SCADA gateway service, and data fusion transport capability. In addition, new application oriented objects such as shop floor, manufacturing line, welding station, robots, and cells have been introduced in the middleware. The combination of such objects and previous modules offers a new and flexible industry oriented middleware. A second contribution is in the form of traffic analysis conducted at the floor level. It shows the dominance of some end systems such as PLCs, the presence well behaved almost constant traffic made up of small packets.     

A new routing algorithm for multirate rearrangeable Clos networks

In this paper, we study the problem of finding routing algorithms on the multirate rearrangeable Clos networks which use as few number of middle-stage switches as possible. We propose a new routing algorithm called the “grouping algorithm”. This is a simple algorithm which uses fewer middle-stage switches than all known strategies, given that the number of input-stage switches and output-stage switches are relatively small compared to the size of input and output switches. In particular, the grouping algorithm implies that m = 2n+(n−1)/2^k is a sufficient number of middle-stage switches for the symmetric three-stage Clos network C(n,m,r) to be multirate rearrangeable, where k is any positive integer and rn/(2^k−1).     

无线有组织网络

无线有组织网络是网络节点间有内在关系的无基础设施的无线网络,其除具有无基础设施无线网络的特征外,网络有中心节点,且节点位置关系相对固定。这种特殊的网络应用于野外救援、军事活动等临时性通信。首先回顾了对讲机系统、无线分组网络和无线自组织网络等无基础设施无线网络的结构和特点,它们都不能包涵无线有组织网络特征。详细定义了无线有组织网的相关模型,分析了无线有组织网络的特点和研究重点。     

神经网络控制结构及所用神经网络

本文阐述了神经网络控制所能解决的控制难题,若干种控制结构及常用的动态神经网络。讨论了神经网络控制研究的重点,在实时控制中的物理可实现性及其发展等问题。     

Banet — a local area network for distributed data processing

A broadcast architecture network (Banet) suitable for distributed data processing is proposed. One feature of Banet is that the broadcast-within-a-group function is supported not only by the datalink level but by the transport or session-level network structure. The commitment control scheme is included in the network protocol. Design goals, physical structure and protocols are discussed.     

多层前向小世界神经网络及其函数逼近

借鉴复杂网络的研究成果, 探讨一种在结构上处于规则和随机连接型神经网络之间的网络模型—-多层前向小世界神经网络. 首先对多层前向规则神经网络中的连接依重连概率p进行重连, 构建新的网络模型, 对其特征参数的分析表明, 当0 < p < 1时, 该网络在聚类系数上不同于Watts-Strogatz 模型; 其次用六元组模型对网络进行描述; 最后, 将不同p值下的小世界神经网络用于函数逼近, 仿真结果表明, 当p = 0:1时, 网络具有最优的逼近性能, 收敛性能对比试验也表明, 此时网络在收敛性能、逼近速度等指标上要优于同规模的规则网络和随机网络.