刍议计算机网络构建技术及故障分析

随着计算机技术及internet的迅速发展,局域网的作用已从最初的主机连接、文件和打印服务,转向围绕着客户机/服务器模式的大数据流应用I、ntranet、WWW浏览等,本文重点介绍网络的构建以及故障分析及维护供同行参考。     

流媒体技术在校园网络教学中的应用

随着时代的不断进步,以多媒体通信技术为基础的流媒体技术的应用也越来越广泛。本文主要探讨流媒体技术在校园网络教学中的应用,介绍流媒体技术的传输基本原理和工作方式,随着信息技术的飞速发展,流媒体的应用得到了快速的发展,在互联网的迅速发展和高校校园网的建设下,如何做好这项工作,是我们当前工作的重中之重。     

移动电子商务产业应用模式创新研究

作为社会信息化与现代服务业的重要组成部分,一个以通信、网络技术为基础的"移动互联新生态"正在世界范围内迅速成长,并酝酿着新一轮的商务革命,移动商务正逐步成为我国电子商务领域的新亮点和主要方向,带来了前所未有的发展新机遇。本文以移动电子商务应用模式为研究对象,系统地分析了移动商务产业链主体特点、利益诉求、合作共赢点及其相互之间的关系,探讨了移动电子商务产业发展的关键命题,提出了三种移动电子商务应用新模式。     

高速铁路测量技术质量控制措施探索

随着我国交通体系的不断完善,高速铁路建设也进入了新的阶段,各个地区都已经形成了较为完善的高速铁路网络,为经济的发展和人们的生活提供了重要的便利。在高速铁路建设过程中应当重视测量技术的应用,基于此本文针对高速铁路建设过程中测量技术精度指标进行了分析,探讨了影响高速铁路测量技术应用质量的因素,并提出了相应的解决措施。     

一种改善数据流间带宽公平性的算法研究

公平性问题是衡量网络性能的重要参数。文章提出了一种新的算法,一方面针对非TCP友好流,利用TCP行为估算每个流的丢包可能性,减少具有不同tRTT(回路响应时间)TCP流之间网络带宽的不公平性问题;另一方面,针对非响应流(如UDP流),该算法将使它在进入路由器之前就丢包。实验结果表明新算法可以降低在网络中的丢包率,同时较好地实现流间带宽的公平分配,从而提高了链路的利用率。     

面向物联网的系统及其网关设计

文章在分析了物联网和云计算特点的基础上,提出了面向物联网的系统,并详细设计了它的应用基础架构、网关结构、信息交互流程,最后阐述了面向物联网系统的应用结构。系统把云计算应用到面向物联网的系统中,降低了系统的成本,实现了接入网络的简单化、标准化。     

分布式存储系统中基于MPI的并行计算编程模型

海量的数据信息对WWW服务器的存储和检索系统提出了较高的要求,同时,互联网技术的发展为开发下一代适合高速发展的新的存储技术奠定了坚实的基础。为此,提出开发新一代基于消息传递编程接口的分布式网络数据存储系统。通过引入并行计算实现分布式存储系统的可靠性及可用性。     

物联网技术在智慧城市建设中的应用

物联网作为新一代信息技术体系中的重要组成部分,将互联网作为信息承载的主体,让所有能够被独立寻址的普通物理对象实现互联互通,这是推动城市现代化发展与建设智慧城市的关键。因此,论文对物联网技术在智慧城市建设领域中的应用现状进行探讨,为相关从业人员提供参考,以期提高物联网技术的应用水平。     

浅析计算机网络教学

在"计算机网络基础"的教学中,网络协议让绝大部分文科学生感到抽象且难以理解,尤其是协议背后所隐藏的网络数据的变化,这直接影响到学生对网络应用软件的使用,因此,理解网络协议十分必要,对此本文进行了论述。     

基于P2P技术的VOD系统研究

由于流媒体数据流具有严格的前后时序关系,多媒体文件又与一般的数据不同,较大的传输负荷将使得网络丢失和拥塞的概率大大增加,因此如何提高音视频传输的服务质量是流媒体技术所面临的最大挑战。文章主要研究流媒体终端系统的服务质量控制,以求在多个上行带宽受限并存储有媒体的节点上利用终端的一些控制策略进行满足播放速率也就是帧率的点播,使用户尽可能享受到好的服务质量并尽量减轻网络的负担。     

第三方应用数据收集过程中隐私保护问题研究进展

不同于传统网络，在移动互联网与云计算环境下，众多的第三方服务依赖于用户数据的收集与分析。如何在保证用户数据安全与隐私的情况下，得到合理的分析与统计结果，一直是网络安全领域研究的热点问题。本文对用户数据隐私保护需求进行了总结，分析了目前在数据收集过程中常用的交集计算相关算法的优缺点，对未来的研究方向做出了总结。     

Sampling frame coverage and domain adjustment procedures for internet surveys

The objective of this paper is to define and compare alternative sampling frames for the representative population coverage as a basis for sample selection in internet surveys. The study aims to provide a methodology for domain weighting and adjustment procedures for free access web surveys that are based on the restricted access surveys. Some basic variables can be proposed for the data adjustment, namely gender breakdown, age groups, and education groups. The application of our work consists of a first stage based on a web survey by an e-mail invitation (restricted access) and a second stage based on a voluntary participation web survey (free access). An advertising company’s registered customer list was taken as the sampling frame population for the first stage. This frame was an electronic e-mail list of the population of registered customers. Two different types of questionnaire were loaded on the company’s internet web site for a month each, for two independent rounds, for testing the visual aspects of the questionnaire design. The restricted access internet survey design relies on probability selection procedures in this study. These results are used with the provided algorithms for the adjustment procedures of free access web surveys. A new methodology is also proposed for the estimation and allocation of the population frame characteristics of adult internet users by gender and age groups. The proposed alternative methodologies will be beneficial tools for future web survey users.     

基于BP网络的企业产品创新状况评价模型

本文提出了一种基于BP网络的企业产品创新状况评价模型，文中对指标体系的构建、神经网络结构的选择、网络学习的算法流程进行了比较详细的介绍，并用实例说明了该方法的具体运用。经检验，该模型的学习能力较强，训练结果比较准确。该模型的建立为评价企业的产品创新状况提供了一条新的途径。     

iSDS: a self-configurable software-defined storage system for enterprise

ABSTRACT

Storage is one of the most important aspects of IT infrastructure for various enterprises. But, enterprises are interested in more than just data storage; they are interested in such things as more reliable data protection, higher performance and reduced resource consumption. Traditional enterprise-grade storage satisfies these requirements at high cost. It is because traditional enterprise-grade storage is usually designed and constructed by customised field-programmable gate array to achieve high-end functionality. However, in this ever-changing environment, enterprises request storage with more flexible deployment and at lower cost. Moreover, the rise of new application fields, such as social media, big data, video streaming service etc., makes operational tasks for administrators more complex. In this article, a new storage system called intelligent software-defined storage (iSDS), based on software-defined storage, is described. More specifically, this approach advocates using software to replace features provided by traditional customised chips. To alleviate the management burden, it also advocates applying machine learning to automatically configure storage to meet dynamic requirements of workloads running on storage. This article focuses on the analysis feature of iSDS cluster by detailing its architecture and design.     

Models for data transmission delay in cable networks

Cable networks have been upgraded in recent years to support bidirectional traffic rather than just unidirectional television signals. Thus, it has become possible to use cable networks for internet browsing and telephony. In this paper, we propose delay models to determine how this bidirectional traffic is best handled and to evaluate the resulting performance of the network, notably its delay properties. It is shown that these models, variations on the repairman problem and the bulk service queue, lead to actual improvements in the data transmission schedules for cable networks. Moreover, these models can be combined in order to arrive at approximations for the average packet delay. Our theoretical calculations are backed up by simulations.     

论我国商业银行的虚拟营销战略模式

计算机技术及信息化网络技术的快速发展,开创了一个崭新的以网络为基础的虚拟经济时代。虚拟银行业务是建立在互联网上的银行,通过网络来开展银行业务。虚拟银行是虚拟经济的一个重要组成部分,在网络经济与信息化电子商务中发挥着重要的作用。虚拟营销战略一方面关注市场迅速变化和需求,另一方面又关注银行自身核心能力的培育和长远发展。     

基于神经网络的框架结构损伤诊断的探讨

利用神经网络技术对框架结构的损伤位置和损伤程度进行了研究。用有限元模态分析技术对平面框架结构的损伤情况进行了模拟,得到一系列频率、竖向位移、水平位移变化数据,将这些数据和损伤位置、损伤程度之间的映射关系作为网络训练样本,解决了以往对于对称结构损伤位置判断的难题,同时提出了用分步输出的方法解决了神经网络技术在框架结构应用中训练速度慢、不易收敛的问题。     

径向基神经网络在木材销售量预测中的应用

基于径向基的神经网络算法在木材销售量预测上的应用,利用历史销售量数据作为样本训练数据,通过径向基的神经网络算法得到的预测值。通过Matlab仿真的结果表明预测值与实际销售量值相比较误差很小。预测数据可作为申请采伐的依据上报给上级国家林业部门,有助于林业管理部门制定更科学的采伐计划,有助于减少贮木场库存,从而提高经济效益。     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.     

Some models for simulating canadian manpower flows and related systems

The paper reports on a series of models designed for computer simulation of Canadian manpower flows at different levels of unemployment, either alone or in conjunction with related population flows. The models are disaggregated macromodels of the state-transition variety. One relates to annual flows, the others to monthly flows.The models have been used for various purposes, including simulation analyses of the effects of changes in economic conditions and government policy variables on two government programs, namely unemployment insurance and manpower training. Other applications are possible and, in general, the basic approach underlying the models is considered to have much potential for manpower policy analysis.