光分组交换网中的一种新模型

目前常用的网络理论模型如曼哈顿网络、洗牌网等均不能适应光分组网络研究的需要.文章提出了一种新的光网络模型———自相似环流网状网.该模型特别适合于光分组网络的研究.文章还研究了该模型的许多特性.     

数据通信网中的自相似模型

本文较为详细地阐述了自相似模型的定义、特性及其在数据通信网中的应用,通过与实际结合来分析传统模型在当今数据通信网中失效的原因,并通过具体的网络性能仿真,对自相似模型和传统模型在仿真结果上的差异进行了比较。     

数据通信网中的自相似模型

本文较为详细地阐述了自相似模型的定义、特性及其在数据通信网中的应用，通过与实际结合来分析传统模型在当今数据通信网中失效的原因，并通过具体的网络性能仿真，以自相似模型和传统模型在仿真结果上的差异进行了比较。     

ASON网状网和SDH环网的经济性比较

文章通过实际网络模型对运用自动交换光网络(ASON)设备组建网状网(mesh)的经济性问题进行了深入研究.根据中国移动骨干传送网现状和预测的2007年业务网需求增长情况,使用网状网容量优化规划工具,仿真分析了使用环网扩容或以不同节点数量引入ASON网状网方案之间的经济性对比,从网络拓扑的角度研究了中国移动骨干传送网向ASON网状网演进的经济性优势.     

基于分形点过程自相似流的队列性能分析

通过对交换机排队系统进行仿真,分析了以分形点过程( FPP )自相似业务流为输入的排队系统的性能.仿真结果显示,自相似业务流量模型下队列的性能与传统指数流量模型下的队列性能大不相同.文中所获得的仿真结果可用于网络流量模型、网络设计、网络拥塞控制和流量工程等.     

宽带卫星Mesh网多址接入信道预测分配方案研究

该文针对具有网状(Mesh)拓扑结构的宽带卫星通信网,研究了分布式控制多址接入信道分配策略。提出了一种基于自相似业务流量混沌预测的混合动态分配方案。利用OPNET软件建立了仿真系统,研究比较了信道分配周期、信道负载以及业务流自相似程度对几种方案性能的影响。仿真结果表明,对于采用地球同步轨道(GEO)卫星、低轨(LEO)和中轨(MEO)卫星星座的宽带卫星Mesh网,所提出方案在高信道负载条件下都具有明显的优势。     

IP over WDM网络联合恢复策略的研究

文章对动态自相似业务在多纤IP over WDM 网中的联合恢复问题进行了系统的研究,提出了3种联合恢复策略,算法的实现基于一种扩展的多纤分层图模型.通过大量的动态仿真实验,以业务中断率和恢复效率为性能指标,研究了上述3种恢复策略在不同自相似参数(突发度、均值和方差)中的性能,最后通过分析和比较得出联合通道恢复策略是最优的.     

通信

TN91 2005020754 数据业务自相似特性研究/宋美娜,段云峰,宋俊德,王进(习晾邮电大 学)11通信学报一2004,25(8)一150一155 合适的业务源模型能够在建立理论分析模型或进行系统性能仿真时,使 网络系统性能评价更加准确.自相似特性是数据业务的重要特征.该文 分析了自相似业务源的建模现状,深入讨论了如何将自相似模型应用于 G PRS业务源建模.通过时间序列自相似特性分析工具SELFis,对 中国移动G PRS网络中从一个网关支持节点GGSN处采集的在单位 时间内收到的字节数进行分析,得出G PRS数据业务具有较强自相似 性的结论.图5表1参19(李)…     

基于PETRI网模型的LEO/MEO/GEO三层卫星网络的性能分析

基于Petri网模型方法和仿真方法,对一种低轨/中轨/同步地球轨(LEO/MEO/GEO)三层卫星网络进行了性能分析.首先建立了卫星网络的广义随机Petri网(GSPN)模型,采用SPNP6.0软件进行了网络性能分析.然后,将分析结果与采用OPNET软件对该三层卫星网络模拟的结果进行了比较,验证了模型的正确性,并得出了诸如在高网络负载的情况下三层网络结构的性能优于单层等新的结论.     

基于EMD及ARMA的自相似网络流量预测

提出了一种基于ARMA(自回归滑动平均)模型的经验模式分解预测自相似网络流量的方法,进行了理论证明和仿真验证.结果表明,经验模式分解对长相关流量有去相关的作用,采用ARMA模型即可对自相似网络流量准确刻画,不但降低了算法的复杂度,而且预测精度高于径向基函数神经网络的预测精度.     

无线传感器网络的安全技术研究

无线传感器网络（WSN）是通过无线通信方式形成的一个多跳自组织网络,是集信息采集、信息传输、信息处理于一体的智能化信息系统。由于其本身资源方面存在的局限性和脆弱性,使其安全问题成为一大挑战。文中分析了无线传感器网络的安全需求、可能受到的安全攻击,给出了防御方法和解决方案。通过安全加密协议、认证流广播和多种密钥机制实现传感器网络的数据机密性、完整性和系统鲁棒性。     

Exploration of the Relation between Input Noise and Generated Image in Generative Adversarial Networks

In this paper, we propose a hybrid model aiming to map the input noise vector to the label of the generated image by the generative adversarial network (GAN). This model mainly consists of a pre-trained deep convolution generative adversarial network (DCGAN) and a classifier. By using the model, we visualize the distribution of two-dimensional input noise, leading to a specific type of the generated image after each training epoch of GAN. The visualization reveals the distribution feature of the input noise vector and the performance of the generator. With this feature, we try to build a guided generator (GG) with the ability to produce a fake image we need. Two methods are proposed to build GG. One is the most significant noise (MSN) method, and the other utilizes labeled noise. The MSN method can generate images precisely but with less variations. In contrast, the labeled noise method has more variations but is slightly less stable. Finally, we propose a criterion to measure the performance of the generator, which can be used as a loss function to effectively train the network.     

Temporal Accountability and Anonymity in Medical Sensor Networks

The increasing number of elderly patients in the world has lead to various new appliances and technologies in the modern tele-healthcare platform. One such application is the medical sensor network (MSN). In this application, patients are deployed with certain medical sensors and wearable devices and are remotely monitored by professionals. Thus, seeing a doctor in person is no longer the only option for those in need of medical care. Since it is also an economical way to reduce healthcare costs and save medical resources, we expect a robust, reliable, and scalable MSN in the near future. However, the time signal and temporal history in the current MSN are vulnerable due to unsecured infrastructure and transmission strategies. Meanwhile, the MSN may leak patients’ identifications or other sensitive information that violates personal privacy. To make sure that the critical time signal is accountable, we propose a new architecture for the MSN that is capable of temporal accountability. In addition, it also preserves privacy ability via a Crowds anonymous system. The analysis results clearly indicate the advantages of being our proposed methods in terms of low-cost and reliable and having scalable features.     

移动社会网络中用户相似性计算的隐私保护研究

移动社会网络（MSN）增强了虚拟世界与现实世界的联系,它允许移动用户发现其现实世界中附近的用户并与之交流。在MSN应用中,为提供更好的服务,通常会比较两个用户的相似性,但在计算用户相似性的过程中很有可能泄露用户的隐私信息。针对这一问题,设计了两种新的相似性计算协议,这些协议保证了在进行相似性计算时不会泄露用户的任何隐私信息。     

Relocation algorithm for non-uniform distribution in Mobile Sensor Network

Energy is the determinant factor for the survival of Mobile Sensor Networks (MSN). Based on the analysis of the energy distribution in this paper, a two-phase relocation algorithm is proposed based on the balance between the energy provision and energy consumption distribution. Our main objectives are to maximize the coverage percentage and to minimize the total distance of node movements. This algorithm is designed to meet the requirement of non-uniform distribution network applications, to extend the lifetime of MSN and to simplify the design of the routing protocol. In addition, test results show the feasibility of our proposed relocation algorithm.     

异构网络中基于移动社交组网的内容传播研究

Since more and more mobile applications are based on the proliferation of social information, the study of Mobile Social Net-works (MSNs) combines social sciences and wireless communications. Operating wireless networks more efficiently by exploiting social relationships between MSN users is an ap-pealing but challenging option for network operators. An MSN-aided content dissemina-tion technique is presented as a potential ex-tension of conventional cellular wireless net-works in order to satisfy growing data traffic. By allowing the MSN users to create a self-organized ad hoc network for spontane-ously disseminating contents, the network operator may be able to reduce the oper-ational costs and simultaneously achieve an improved network performance. In this paper, we first summarize the basic features of the MSN architecture, followed by a survey of the factors which may affect MSN-aided content dissemination. Using a case study, we demon-strate that one can save resources of the Base Station (BS) while substantially lowering content dissemination delay. Finally, other potential applications of MSN-aided content dissemination are introduced, and a range of future challenges are summarized.     

基于凝聚子群分析的MSN监控系统

论文将社会网络的派系分析思想引入到MSN通信系统的内容过滤和分析中,从社会网络分析中凝聚子群的角度对以MSN构成的网络进行详细的分析,通过对凝聚子群和关键节点的分析,提取派系划分,派系首领和重要参与者等有效信息,以实现对MSN通信网络中不良内容的有效监控和阻断。     

基于动态MSN的软交换多业务环境性能研究

在下一代网络中将提供具有不同性能要求的语音、数据和多媒体业务,研究这些业务性能的相互影响并采用有效的方法保证这些业务的性能指标对下一代网络的成功实施具有重要意义.本文设计了一种多队列的软交换多业务控制框架,在此基础上提出并分析了一种动态最大会话数(MSN,Maximum Session Number)方法来分配系统资源,以有效利用系统资源确保业务性能.仿真结果表明:在软交换多业务环境中,采用动态MSN方法能确保系统的稳定性并有效地满足各种软交换业务的性能要求.     

局域网即时通信监控系统的研究与实现

针对目前广泛使用的即时通信软件MSN的安全问题,在具体分析其通信协议的基础之上,设计了专门的监控系统。该系统以监控局域网络为目的,主要针对MSN的文本信息进行监控。最后对设计的系统进行了性能测试,测试结果显示该系统具有良好的性能,系统可以在不改变现有网络配置、不影响网络运行效率的前提下,满足局域网对MSN的通信内容进行监控的需求。     

Survey on mobile social networking in proximity (MSNP): approaches,challenges and architecture

Recently, mobile social networks (MSN) have gained tremendous attention, which free users from face-to-monitor life, while still can share information and stay in touch with their friends on the go. However most MSN applications regard mobile terminals just as entry points to existing social networks, in which centralized servers (for storage and processing of all application/context data) and continual Internet connectivity are prerequisites for mobile users to exploit MSN services, even though they are within proximity area (like campus, event spot, and community, etc.), and can directly exchange data through various wireless technologies (e.g., Bluetooth, WiFi Direct, etc.). In this paper, we focus on mobile social networking in proximity (MSNP), which is explicitly defined in our paper as: MSNP is wireless peer-to-peer (P2P) network of spontaneously and opportunistically connected nodes, and uses geo-proximity as the primary filter in determining who is discoverable on the social network. In this paper, first, primary support approaches related to MSNP available in literature, are summarized and compared, including MSN, mobile P2P and opportunistic networks. And then, we offer the special characteristics of MSNP, open issues and potential solutions. A networking technologies and platform independent architecture is proposed for developing MSNP applications, and proof-of-concept implementation of WiFi direct based MSNP application is also provided. Our primary goal is to identify the characteristics, technical challenges and potential solutions for future MSNP applications, capable to flexibly adapt to different application domains and deployment requirements.