一种适用于分层卫星网络的区分服务模型

分层卫星网络（MLSN）是下一代卫星网络的主要发展方向,其QoS问题成为制约其发展的重要瓶颈。本文从现有地面网络中的QoS模型出发,结合MLSN的特性,提出了一种适用于MLSN的QoS模型MLSN—DiffServ。该模型充分利用了区分服务中DSCP和PHB的概念以及MLSN的分层体系结构和多星选择接入机制,通过扩展DSCP和PHB的概念及实现方式,实现了一种适合MLSN的区分服务模型,仿真结果证明,该模型不仅可以应用于MLSN,而且有良好的性能表现。     

Dynamic Game Theoretic Model of Multi-Layer Infrastructure Networks

Due to similarities in terms of network structure and interactions among them, most infrastructure systems can be viewed as coupled layers of a generalized transportation network in which the passenger, freight, data, water, and energy flows are the commodities in the different layers. The coupling is due to the varying degrees of interactions among these layers in terms of shared physical networks, budgetary constraints, socio-economic environments, environmental concerns, information/other resources, and in particular, functional interdependencies. However, these interactions are normally ignored in the engineering planning, design and analysis of infrastructure systems. Identifying and understanding these interactions using a holistic perspective can lead to more efficient infrastructure systems. This paper presents a preliminary network flow equilibrium model of dynamic multi-layer infrastructure networks in the form of a differential game involving two essential time scales. In particular, three coupled network layers—automobiles, urban freight and data—are modeled as being comprised of Cournot-Nash dynamic agents. An agent-based simulation solution structure is introduced to solve the flow equilibrium and optimal budget allocation problem for these three layers under the assumption of a super authority that oversees investments in the infrastructure of all three technologies and thereby creates a dynamic Stackelberg leader-follower game.     

相互依存网络边攻击下的相继故障研究

许多现实的网络彼此间相互作用与依存,一个或几个网络的故障将导致网络间的相继故障,最终导致相互依存的网络系统整体失效.为解决边攻击下的相互依存网络的相继故障及其渗流问题,提出一个理论框架,运用生成函数和渗流理论,分析边攻击下的相互依存网络的相继故障渗流及其结果.并以相互依存的随机网络和无标度网络作为实例,进行实例分析与仿真实验.仿真结果与理论分析相符并表明:相比于单独网络,随机边攻击下的相互依存网络因其广度度分布增加了其脆弱性,且故障渗流相变为一级相变;相互依存的无标度网络的鲁棒性比相互依存的随机网络的鲁棒性差,其原因是相互依存的无标度网络中存在一个网络中的小度节点连接另一网络的大度中心节点引起网络间故障级联面的增大.     

关于无线传感网络演化模型抗毁性分析

抗毁性是评价无线传感网络拓扑结构的重要性能之一,如何构建一个健壮的网络显得尤为重要.基于复杂网络理论,提出一种关于节点度、剩余能量、传输距离的网络演化模型,简称DEDA.同时引入了几种适合无线传感网络的指标来评价网络的抗毁性.利用计算机仿真技术,比较了不同模型演化所形成的网络拓扑结构在随机和故意攻击下的抗毁性.实验结果表明,DEDA模型演化形成的无线传感网络在随机攻击和故意攻击下提供了更好的抗毁性.     

关联基础设施网络模型研究综述

随着人类社会日益复杂化,人们对各种关乎国计民生的关联基础设施网络的安全性和可靠性提出越来越高的要求.关联基础设施网络的模型自然成为了研究焦点之一.对关联基础设施网络的模型研究和应用现状进行了归纳总结,分析了几种有代表性的模型,最后提出了现有的问题和未来的研究方向.     

跨网段多层交换网络下的数据群发研究

本文介绍了一种基于TCP协议的数据群发方案,该方案适用跨网段多层交换网络中的数据传输,需接收数据的机器只要都通过交换机连接,能用IP地址唯一标识即可.实验证明,该方案保证了群发数据所需时间随着数据的增大只是线性增加,在网速一定时,基本与需要接收数据机器的数量成对数级的关系,网络资源也得到了充分的利用.     

Single-Iteration Training Algorithm for Multi-Layer Feed-Forward Neural Networks

A new methodology for neural learning is presented. Only a single iteration is needed to train a feed-forward network with near-optimal results. This is achieved by introducing a key modification to the conventional multi-layer architecture. A virtual input layer is implemented, which is connected to the nominal input layer by a special nonlinear transfer function, and to the first hidden layer by regular (linear) synapses. A sequence of alternating direction singular value decompositions is then used to determine precisely the inter-layer synaptic weights. This computational paradigm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information transfer within a neural network. Examples show that the trained neural networks generalize well.     

相互依赖网络的多参数混合幂次迭代瓦解策略

探寻复杂网络的最优瓦解策略是网络科学研究中的重要课题.相比于单层网络,更为普遍的多层耦合网络的最优瓦解成为新的研究方向.传统算法大多集中在研究高中心性节点,而单一的中心性测度往往会导致对节点重要性的评估出现偏差.首次结合质量扩散(MD)和热传导(HC)两种经典物理方法,提出了一种新的基于幂次迭代的算法(PIA),该方法...     

一种高能效的无线传感器网络模型

在分析集中式体系结构和分布式动态体系结构基础上,提出了一种提高目标跟踪无线传感器网络使用寿命的模型,该模型是一个静态簇型架构,由异构传感器组成,传感集群中的每个成员节点采用两种运作模式:工作模式和睡眠模式.结果表明,所提出的架构比集中式系统消耗更少能源,而且使用寿命更长.     

Efficient Training of Multi-Layer Neural Networks to Achieve Faster Validation

Artificial neural networks (ANNs) are one of the hottest topics in computer science and artificial intelligence due to their potential and advantages in analyzing real-world problems in various disciplines, including but not limited to physics, biology, chemistry, and engineering. However, ANNs lack several key characteristics of biological neural networks, such as sparsity, scale-freeness, and small-worldness. The concept of sparse and scale-free neural networks has been introduced to fill this gap. Network sparsity is implemented by removing weak weights between neurons during the learning process and replacing them with random weights. When the network is initialized, the neural network is fully connected, which means the number of weights is four times the number of neurons. In this study, considering that a biological neural network has some degree of initial sparsity, we design an ANN with a prescribed level of initial sparsity. The neural network is tested on handwritten digits, Arabic characters, CIFAR-10, and Reuters newswire topics. Simulations show that it is possible to reduce the number of weights by up to 50% without losing prediction accuracy. Moreover, in both cases, the testing time is dramatically reduced compared with fully connected ANNs.     

用多隐层BP网实现的CRT色度变换

为了实现彩色信息的标准化显示,需要对ＣＲＴ的色度空间进行标定,也就是ＣＲＴ的Ｒ、Ｇ、Ｂ空间与ＣＩＥ的标准色度空间的相互转换问题,人工神经网络近年来被广泛应用于多种颜色空间的变换过程中,在分析前人经验的基础上,提出了一种采脾四隐层ＢＰ网的ＣＲＴ的Ｒ、Ｇ、Ｂ与ＣＩＥ的Ｘ、Ｙ、Ｚ色度空间的变换方法,实验结果表明,该方法的收敛性和训练时间均优于前人采用２个或３个隐层的方案,而且通过对５１２个训练样本的实验     

基于策略的异构网络多层QoS管理体系研究

目前通信网络呈现出多样化、冗余化、异构化的特点,在这样的网络环境下存在端到端的传输质量问题。在研究QoS管理和策略管理框架的基础上,介绍了常见的QoS管理框架和基于策略的QoS管理的概念及基本思想;分析了异构网络环境下端到端QoS保证面临的问题;提出了基于策略的异构网络互联多层QoS管理体系,通过在无线网络中设置无线域策略决策点和无线域策略执行点来支持新的独立的策略域,并着重对策略域层次间的协商交互过程进行了描述。     

电力基础设施网络级联毁伤传播算法

级联毁伤是对电力基础设施网络局部打击引发的毁伤传播和大面积级联瘫痪现象,实际为具有依赖关系的实体之间的行为交互和毁伤传播过程.为仿真研究战争危机条件下的电力基础设施网络毁伤综合效果,依据复杂系统实体的交互依赖关系和毁伤传播机理,设计实现了电力基础设施网络节点级联依赖度生成算法和级联毁伤传播算法.通过实例计算分析和仿真,结果较好地体现出电力基础设施网络级联毁伤的动态演化过程,有效满足了战争仿真中对上述类型网络毁伤综合效果的分析需求.     

面向核心网的多层网络能耗优化方法

随着网络规模和流量的迅速增长,Internet的能耗问题变得日益严重.文中研究IP(Internet Protocol)over TDMoverWDM核心网的能耗问题,首先对多层网络的节能机制进行了分析,在此基础上,提出了一种多层网络能耗优化的ITO模型,充分考虑多层网络的体系结构和网络设备的模块化特性,协同使用网络业务流控制和网络资源配置与管理的方法,实现业务流在多个网络层合理的分配和路由以及网络设备的多粒度模块睡眠,以达到降低网络能耗的目的.实验结果表明,ITO模型能有效降低网络的能耗,在网络业务量较低时,可将网络功耗降到业务高峰期时的24％～38％.此外,该文还通过实验探讨了业务的疏导和旁通、不同的网络层组合、网络设备的动态功耗以及网络设备的模块化结构对网络能耗优化的影响,为构建节能高效的绿色网络提供了参考.     

Designing Connection Oriented Networks for Multi-Domain Path Resilience

A challenge in network management and control is the ability to account for multi-domain requirements in the network planning process. Especially in Connection Oriented Networks where multi-domain path finding is a critical issue, networks need to be designed in such a manner as to restrict the possibility of erroneous inter-domain path selection. In this paper we propose per-domain topology design considerations that would leverage accurate disjoint path computations in a multi-domain environment, covering requirements of end-to-end path resiliency. In multi-domain environments state information between domains is heavily aggregated, hiding internal topology details dictated by scalability concerns, but also by restrictive domain administration policies for privacy, and security. Disjoint path finding is strongly affected by the aggregation techniques, since they do not provide information on path overlap. To handle this issue we introduce a metric, the Overlap Factor (OF), that quantifies path overlap in domains. The OF can be passed as an additional parameter of the inter-domain information exchange model to evaluate disjoint end-to-end paths. Alternatively, if domains were appropriately designed, this additional parameter might not be needed in evaluating resilient pairs of inter-domain paths. We based our recommended topology design algorithm on exploiting locally known OF values within the context of Genetic Algorithms. Extensive simulations confirm that domains designed using our proposed algorithm, result into accurate multi-domain disjoint path identification, with a high success ratio compared to networks that are designed without inter-domain considerations.     

动态不确定环境下的决策：一种分层决策模型

本文提出一种智能体分层决策结构模型，试图通过分层决策技术有效地解决动态、不确定环境中的智能体的实时决策问题。本模型的高层采用BDI结构，以便为较长期任务的规划和推理提供充分的支持；模型的底层采用反应式结构，以保证对短期实时任务的及时响应。实验结果表明了这种分层模型在某些复杂任务领域中的有效性。     

生产信息系统的多级安全策略模型

生产信息系统是一类对安全要求较高,有明确安全目标,专为工程应用定制的信息系统.它有明确的边界环境,相对固定的应用流程和用户角色以及大量的先验安全知识.为了开发安全的生产信息系统,首先必须建立系统的安全模型.提出的生产信息系统的多级安全策略模型,在遵守最小特权的原则下,将主客体安全属性、操作请求、安全策略和行为环境综合考虑,引入完整性检查引擎和保密性检查引擎,将主体从授权可信过渡到行为可信.其实现思路对于安全生产信息系统的建立提供了很好的参考价值.     

基于Java的多层系统模型研究

分析了传统体系结构的不足,提出了多层应用系统在Java中的实现模型.同时,由于Java具有跨平台、可移植性、安全高效等强大功能,是开发多层应用系统的理想工具.     

An Equitable Bandwidth Allocation Model for Video-on-Demand Networks

Video-on-Demand (VOD) or near-VOD services are expected to grow significantly over time, providing diverse programs for home entertainment, learning and training, news-on-demand, and other applications. These services require large bandwidth resources. We present a model for bandwidth allocation in a tree network with limited link capacities, where a server at the root node repeatedly broadcasts copies of various programs. The time intervals between successive broadcasts of each program can be increased at subsequent nodes, or the video quality can be decreased, thus providing different service performance to different nodes while satisfying the capacity constraints. The model is formulated as an equitable resource allocation problem with a lexicographic minimax objective function and tree-like ordering constraints. We present a lexicographic minimax algorithm that allocates each link’s bandwidth among the programs carried on the link. The algorithm repeatedly solves minimax problems, and fixes some variables at their optimal value after the solution of each such problem. The algorithm for solving the minimax problems uses a bisection search to find the minimax solution with the minimal decision variable values. The model also provides an ordered list of links from the most critical link to the least critical link, a useful feature for capacity expansion planning decisions.