MORM: A Multi-objective Optimized Replication Management strategy for cloud storage cluster

Effective data management is an important issue for a large-scale distributed environment such as data cloud. This can be achieved by using file replication, which efficiently reduces file service time and access latency, increases file availability and improves system load balancing. However, replication entails various costs such as storage and energy consumption for holding replicas. This article proposes a multi-objective offline optimization approach for replica management, in which we view the various factors influencing replication decisions such as mean file unavailability, mean service time, load variance, energy consumption and mean access latency as five objectives. It makes decisions of replication factor and replication layout with an improved artificial immune algorithm that evolves a set of solution candidates through clone, mutation and selection processes. The proposed algorithm named Multi-objective Optimized Replication Management (MORM) seeks the near optimal solutions by balancing the trade-offs among the five optimization objectives. The article reports a series of experiments that show the effectiveness of the MORM. Experimental results conclusively demonstrate that our MORM is energy effective and outperforms default replication management of HDFS (Hadoop Distributed File System) and MOE (Multi-objective Evolutionary) algorithm in terms of performance and load balancing for large-scale cloud storage cluster.     

不同老化方式对沥青低温性能的影响分析

研究了不同老化方式对沥青低温性能的影响,分3个阶段,对不同老化方式的试验结果进行了比较.阶段1研究表明,沥青在压力老化容器(PAV)中100℃条件下老化20 h后的低温性能与在1.01×105Pa、60℃条件下老化38 d后的低温性能相差无几.阶段2研究表明,可以通过58℃、10 r/s时的高温因子G*/sinδ来修正低温性能分级,从而可以利用短期老化来代替长期老化试验.阶段3研究表明,沥青的低温性能会随着老化时间改变而变化.当老化时间较短时,低温性能分级由劲度指标控制;当老化时间较长时,低温性能分级将转变为由蠕变速率控制.     

Real-time facial animation on mobile devices

We present a performance-based facial animation system capable of running on mobile devices at real-time frame rates. A key component of our system is a novel regression algorithm that accurately infers the facial motion parameters from 2D video frames of an ordinary web camera. Compared with the state-of-the-art facial shape regression algorithm [1], which takes a two-step procedure to track facial animations (i.e., first regressing the 3D positions of facial landmarks, and then computing the head poses and expression coefficients), we directly regress the head poses and expression coefficients. This one-step approach greatly reduces the dimension of the regression target and significantly improves the tracking performance while preserving the tracking accuracy. We further propose to collect the training images of the user under different lighting environments, and make use of the data to learn a user-specific regressor, which can robustly handle lighting changes that frequently occur when using mobile devices.     

A global energy optimization framework for 2.1D sketch extraction from monocular images

The 2.1D sketch is a layered image representation, which assigns a partial depth ordering of over-segmented regions in a monocular image. This paper presents a global optimization framework for inferring the 2.1D sketch from a monocular image. Our method only uses over-segmented image regions (i.e., superpixels) as input, without any information of objects in the image, since (1) segmenting objects in images is a difficult problem on its own and (2) the objective of our proposed method is to be generic as an initial module useful for downstream high-level vision tasks. This paper formulates the inference of the 2.1D sketch using a global energy optimization framework. The proposed energy function consists of two components: (1) one is defined based on the local partial ordering relations (i.e., figure-ground) between two adjacent over-segmented regions, which captures the marginal information of the global partial depth ordering and (2) the other is defined based on the same depth layer relations among all the over-segmented regions, which groups regions of the same object to account for the over-segmentation issues. A hybrid evolution algorithm is utilized to minimize the global energy function efficiently. In experiments, we evaluated our method on a test data set containing 100 diverse real images from Berkeley segmentation data set (BSDS500) with the annotated ground truth. Experimental results show that our method can infer the 2.1D sketch with high accuracy.     

浅析电厂锅炉运行效率的影响因素及对策

在电厂运行中,锅炉是最重要的设备之一,它与整个电厂的安全、稳定运行有着密切的关系,因此,提高电厂锅炉的运行效率是保证电厂长远发展的有效途径。分析了影响电厂锅炉运行效率的因素,提出了提高电厂锅炉运行效率的对策,以期能够促进电厂经济效益的不断提高。     

基于串空间认证测试的DTLS协议认证性分析

网络通信的普及和发展使得对网络协议尤其是安全协议的需求日益增长,同时安全要求及攻击方式的多样化对网络安全协议的效率和准确性提出了更高的要求。通过对各种协议安全性分析方法进行研究,采用串空间方法对DTLS协议进行形式化建模,进而采用认证测试方法进行协议认证性证明,用简明清晰的方式验证DTLS协议的认证性,保障了数据传输的安全。     

硬件中断引入方法及中断深度性能测试

讨论了Windows操作系统下硬件中断产生的方法,使用硬件DIO输出卡对设计的中断服务程序作了多种时序下试验,做了Windows系统下中断服务工作时的干扰试验,在中断线程和工作线程内部提出了多种试验方法,深入研究了Windows系统下的内核级调度执行相关代码段所需的时间,测试了多种时钟的精确度,设计了工程实用的中断服务程序。     

基于用户QoE的流媒体系统性能测评模型设计

影响流媒体用户服务质量体验QoE(Quality of Experience)的因素有很多,如何对用户QoE进行量化判别是一个复杂的问题。为此,以媒体传输指标MDI为基础,研究了用于测量流媒体用户QoE的基本指标,并提出了相关测量数据的获取方法。以流媒体用户的实际体验质量为依据,提出了一种有效的流媒体系统性能评价模型,该模型为流媒体系统的性能分析和优化调整提供了理论基础,具有广泛的应用价值。     

基于Flash 3D的在线虚拟漫游系统设计与实现

对目前虚拟漫游系统的瓶颈进行分析,提出并实现了一个基于Flash 3D的、优化了的在线虚拟旅游系统。系统对三维场景文件包括模型文件、材质文件及其构建步骤进行优化,并在实现了对多种媒体元素支持的基础上,设计了独创的热点系统,实现对三维场景按需进行加载和展示,以及游客在场景中的互动漫游。系统测试结果表明,该设计方案优化效果显著,系统性能得到了极大的提升。     

虚拟机软件结合LoadRunner的一种测试方案探讨

基于虚拟化技术进行软件自动化测试是测试主流技术发展的一个方向。介绍了虚拟机软件VMware结合测试工具软件LoadRunner的一种软件测试方案,详细介绍了测试方法、测试环境、测试用例以及数据处理方法。通过对同一B/S系统在真实环境和虚拟环境中进行对比性能测试,并基于实测数据加以分析,论证了该方案的优越性,得出了能否应用的结论。