基于用户行为特征的P2P视频点播系统数据预取机制

随机搜索是用户在享受视频点播服务时常见的行为,它使得播放进度发生突然变化,同时要求系统做出及时的响应.为了缩短数据访问的响应时延,通常采用预取机制提前获取部分数据用以满足将来的需要,然而如何利用有限的存储空间预取尽可能多的有用数据是其中的关键问题.本文根据视频点播用户随机搜索操作的行为特征模型和媒体内容不同部分受欢迎程度的不同,提出一种范围受限、流行度感知的P2P视频点播系统数据预取机制RC-PAP.仿真实验结果表明,相比于现有的数据预取方法,RC-PAP 可以显著提高用户随机搜索操作时的响应速度,并减轻内容源服务器的访问压力.     

面向多租约SaaS应用的负载均衡机制研究与实现

随着云计算的普及,SaaS作为一种新的软件交付模式得到了越来越广泛地关注.为了支持高速业务发展带来的大量用户的访问请求,多租约SaaS应用需要负载均衡机制以支持可扩展性.本文从对多租约SanS应用用户需求的分析入手,提出了一种面向租约功能类型的服务器负载模型和面向租约用户非功能需求的执行请求按需分配算法,设计了一个面向多租约SanS 应用的负载均衡系统.实验表明本文提出的面向多租约SaaS应用的负载均衡机制能在满足不同租约用户需求的同时提高系统整体执行效率.     

一种自适应的数据预取与缓冲算法

在海量数据中进行的直接查找往往耗时巨大,在实际应用中很难满足实时性的需求,因此采用数据预取和缓冲技术实现对查找操作的优化成为实际系统中的重要环节。自适应的数据预取和缓冲算法是通过使用人工智能中的技术来分析用户的查询习惯,从而实现动态的预取策略并对预取的数据进行缓冲,以达到提高查询速度的目的。文章根据不同的数据查询需求提出了两类智能算法以适应不同的应用场合。在实验中分别针对单个用户的历史查询应用和多用户的并发查询应用分别进行了分析,证明了这两类智能算法分别对不同的应用场合拥有较好的性能。     

实时主动数据仓库中面向需求的实时数据集成方法研究

实时数据集成是实时主动数据仓库研究领域的一个重要问题.现有的研究成果都是从技术角度出发,而并没有考虑具体的商务应用需求.而在大型商务应用中,即使采用过滤规则只捕捉感兴趣的变化数据,也会产生大量的数据集成工作,从而导致不必要的沉重系统开销,同时还很有可能出现系统响应缓慢和用户需求无法得到满足等情况.从应用角度出发,提出了实时主动数据仓库中面向需求的实时数据集成方法,包括被频繁请求的数据的实时集成、满足突发请求的实时数据集成和由用户决定的实时数据集成.针对不同的商务需求,采用不同的数据集成策略,可以很好地满足不同类型的应用需求.     

移动环境下支持实时事务处理的数据预取

随着移动通信技术的迅速发展,人们提出了新的应用要求:在移动环境下处理实时事务.而移动通信带宽有限性引起较大的数据访问延迟,有时甚至由于网络传输的断接使得事务得不到所需要的数据,数据预取能够很好地解决这个问题.已有的移动环境下数据预取没有考虑到数据的流行性和事务的时间特性.该文分析影响实时事务数据预取的因素,首先考虑数据易变性、活跃性等因素,获得高价值预取数据集合;然后考虑访问预取数据的事务优先级、数据流行性等因素,构造预取数据的选择函数,通过该函数在前面选取的集合中筛选出对满足实时事务截止期更有价值的数据对象进行预取.实验表明,该数据预取策略能降低移动实时事务满足截止期的比率,更好地支持移动实时事务处理.     

虚拟机环境下软件按需部署中的预取机制

针对大规模虚拟机环境下软件的按需部署,提出了一种基于预取的按需软件部署优化机制,能够降低用户端虚拟机的启动延迟以及为用户提供更好的虚拟机本地运行性能.基于用户使用软件的行为特点以及虚拟磁盘映像的细粒度分割,预取机制在后台对服务器端存储的虚拟磁盘映像进行预取,通过一种基于访问频率和优先级的预取目标识别算法AFPTR(access frequency and priority-based prefetch target recognition)和一种预取量动态调节机制,将预取集中在用户使用的少数小尺寸的虚拟磁盘映像上,并在预取过程中对预取量进行动态自适应地调节,以提高虚拟磁盘访问的本地命中率,进而提高用户端虚拟机的运行性能.基于QEMU虚拟机和Linux平台,实现了基于预取的按需软件部署原型系统.实验结果表明,预取机制能够有效地降低虚拟机的启动延迟,并能提高虚拟机的本地运行性能,支持虚拟机环境下按需、快速的软件部署.     

支持软件按需流式加载的预取机制

近年来,随着SaaS技术的发展,软件的网络化、服务化访问成为一种新的使用模式.软件的按需动态部署是实现上述模式的重要基础.为了支持软件的按需动态部署,需要能够在执行环境支持软件的流式加载运行.而在软件按需流式加载的执行过程中,程序会因为请求缺失的数据块被阻塞直至数据块被下载过来,从而极大地影响执行性能与用户体验.针对流式加载中的性能问题,提出一种基于N-Gram预测模型和增量数据挖掘技术的预取机制,该预取机制可用于支持软件流式加载执行.预取机制通过收集用户使用软件所产生的历史访问日志,进行数据挖掘分析,来动态更新、完善预取规则,然后根据最合理的预取规则进行软件预取.该预取机制可同时支持基于文件级别和软件块级别的预取.实验结果表明,对于各类软件,该可预取的文件系统能够将软件启动加载时间减少10%～50%,而预取命中卒达到了81%～97%.     

一种智能终端数据共享中的预取缓存技术

针对智能终端数据共享中的网络延迟问题,本文提出一种两阶段,主动预取与被动预取相结合的数据预取缓存方法,减少网络延迟,提高用户体验。该方法利用网络空闲时间预取数据,减少用户等待时间;通过两阶段预取策略减少网络带宽消耗;通过主被动配合的预取算法来预取数据,提高预取准确率和预取效率;通过一种权重更新函数来更新客户端的缓存,减少对智能终端存储空间的消耗。实验表明使用此方法能减少用户等待时间58.2%,预取命中率为92%,带来的带宽损耗小于5%。     

基于时延分析的AFDX智能网络管理模型全局调度算法研究

为了更好地解决航空电子AFDX网络在应用上的不确定性问题,通过对AFDX网络时延进行分析,在建立AFDX智能网络管理模型的基础上提出了全局调度算法,该算法从AFDX网络全局角度出发,动态实时地调整调度算法、平衡网络负载,通过NS-2进行网络仿真,结果显示此算法能够有效地减少数据的最大延迟抖动,明显提高了AFDX网络的数据传送效能,更好地满足了航空电子网络数据传输的实时性要求,使AFDX网络运行更加高速可靠.     

面向主干网的网络级绿色节能机制

近些年,全球范围内的互联网高能耗问题引发了持续关注,节能已成为未来互联网研究的热门议题之一.面向主干网,提出一种网络级绿色节能机制：一方面,在全局视图中使用最小剩余容量优先的绿色路由算法规划全局路由路径,这样使得网络中开启的捆绑链路数目最小,从而实现第一步节能;另一方面,在局部视图中使用绿色降序最佳适应算法将流量负载汇聚到捆绑链路中的最小物理链路集合,这样可以尽可能多地关闭物理链路,从而实现进一步节能.提出的机制在节能的同时兼顾用户QoS需求的满足,在提供QoS保证的前提下最大化节能收益.为了全面评估该机制,选取3个典型主干网拓扑：CERNET2,GéANT和INTERNET2,分别在高负载、中负载和低负载的情形下,与其他3种节能机制从网络功耗和网络性能（平均路由跳数、物理链路关闭数目、路由成功率和运行时间）方面做详尽的对比分析.仿真结果表明：该机制节能效果显著,且有令人满意的性能表现.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。