基于Windows运行过程可视化的软件性能分析

为了重现系统运行时各个进程/线程的运行状态、相互间的交互状况以及对CPU和磁盘的资源占用情况,首先以事件跟踪的方式采集正在运行的Windows操作系统的内核数据并加以解析,再输入到可视化工具输出图形界面。通过可视化工具来定位影响程序性能的瓶颈,分析引起性能问题的原因,确定优化的方向,以实现软件开发预期的性能指标。最后展示了一个软件性能优化的实例。     

Windows内核恶意代码分析与检测技术研究

Windows内核恶意代码是指能够通过改变Windows执行流程或者改变内核审计和簿记系统所依赖的数据结构等手段以达到隐藏自身,实现恶意功能的程序或程序集,对操作系统安全造成很大的危害.对近年来基于NT内核的微软Windows操作系统下恶意代码主要的隐藏实现技术(包括对进程函数、注册表函数、SSDT等的HOOK行为)进行了深入分析研究,提出了一些具有实用价值的恶意代码检测技术方案.实践表明文中提出的恶意代码分析检测技术在实际中具有积极的指导意义.     

Windows内核恶意代码分析与检测技术研究

Windows内核恶意代码是指能够通过改变Windows执行流程或者改变内核审计和簿记系统所依赖的数据结构等手段以达到隐藏自身,实现恶意功能的程序或程序集,对操作系统安全造成很大的危害。对近年来基于NT内核的微软Windows操作系统下恶意代码主要的隐藏实现技术（包括对进程函数、注册表函数、SSDT等的HOOK行为）进行了深入分析研究,提出了一些具有实用价值的恶意代码检测技术方案。实践表明文中提出的恶意代码分析检测技术在实际中具有积极的指导意义。     

一种新型内核扩展安全访问方法

内核扩展的安全性对操作系统的稳定运行具有重要意义.内核扩展在为驱动开发提供了便捷的同时,但也带来了重大安全隐患.本文设计了一个新型内核扩展安全访问(Security Access to Kernel Extension,SAKE)模型系统,该系统通过对驱动模块的控制范围进行约束,对关键内核扩展函数接口进行审查,来实现安全的内核扩展访问.文中所述研究在Linux操作系统上对SAKE模型系统进行了实现,并结合多款驱动进行了评测.安全性评测结果表明SAKE能够提供安全内核扩展访问功能,并且性能评测表明该系统带来的开销很小.     

Linux内核中进程调度的分析

进程是让操作系统实现程序的并发执行,系统资源共享,用户随机使用系统等功能的重要概念。文章首先介绍进程在Linux内核中的表示方式,然后结合源代码深入分析进程的时间片轮转,先进先出,Round robin调度策略的具体实现,对我们进一步了解Linux内核的工作机制和学习编程均有较好的实用参考价值。     

面向移动Web应用的浏览器缓存性能度量与优化

随着移动互联网的飞速发展,用户越来越多地通过移动设备访问Web应用.浏览器为Web应用提供基本的计算、渲染等运行时支撑,其缓存机制可以支持Web应用直接从本地而不是通过网络来获取可复用资源,不仅能够减少整体的执行时间从而提升应用加载速度,还能够减少网络流量使用和电池电量消耗,从而保证移动Web用户体验.近年来,围绕面向移动Web应用的浏览器缓存优化得到了国内外学术界和工业界的广泛关注.然而,现有研究工作大多都是从网络层面关注浏览器缓存的整体性能,未充分考虑移动互联网用户访问行为的差异性和动态性,以及Web应用自身持续演化对浏览器实际缓存性能的影响.针对这一问题,首先设计了一种新型主动式缓存度量实验,通过仿真用户的访问行为来分析移动Web应用实际资源使用情况,揭示了浏览器缓存的理论性能上限和实际性能之间的巨大差距,并发现了造成这一差距的3个主要原因：重复请求别名资源、启发式过期时间和保守的过期时间配置.基于此发现,从应用层和平台层分别提出了两种浏览器缓存性能优化方案,并实现了原型系统.实验结果表明,采用两种方法分别平均可减少8%~51%和4%~58%的网络流量,且系统开销较小.     

基于Web的ACM/ICPC自动评测系统的设计与实现

针对现有ACM程序设计竞赛评判系统存在的缺陷,采用了新的架构模式,设计了用于大学生程序设计训练和竞赛的自动评测系统,实现了对用户提交的程序源代码进行自动编译、连接、运行、测试、评审等过程并返回测试结果,采用了多进程的并发处理、信号处理、进程通信、文件管理等技术,使得该自动测评系统在实际应用过程中发挥良好的性能,完成了日常编程训练和各类网上程序设计竞赛活动,体现了竞赛过程的自动化、高效率、公正性等特性。     

资源有限的微云服务模型研究

微云是一种自我维持的小型云,通过均衡用户的访问请求来提高移动服务的整体性能,但在实际应用中分散的用户需求会随时间动态变化,而服务资源需要根据请求预测情况进行提前部署。为优化微云服务模型的整体资源利用率,基于排队论构造符合生灭过程的微云有限资源服务模型,对比微云上单队列和多队列模型的性能指标,得出单队列多虚拟内核模型在相同服务强度的情况下优于多队列单虚拟内核模型的结论。实验结果表明,在适当增加虚拟内核的情况下,该微云服务模型可以优化系统整体性能。     

基于嵌入式Linux系统的内核级线程库的研究与实现

在当前嵌入式系统应用中,性能问题一直是人们关注的重点.大多数嵌入式Linux应用往往运行在用户态,系统运行时需要经常在内核态和用户态之间反复切换,降低了关键业务的执行效率.以往的研究较少从内核态下的线程库出发来考虑性能优化的实现方法,影响了嵌入式系统的整体性能.对此,本文提出一种适用于嵌入式Linux系统的内核级线程库(LKTL),并且分析了实现的关键技术.LKTL提供了线程管理、信号量同步、内存的动态分配和回收、日志管理以及基本的GNU C库的功能,不但大大提高了应用程序的运行效率,还方便了应用程序的开发和移植.实验表明LKTL能够显著优化嵌入式Linux系统的整体性能.     

基于用户行为的长查询用户满意度分析

搜索引擎性能评估是信息检索界一个重要课题.长查询具有较为丰富的信息内容,能更加准确地描述用户的信息需求.在此基础上文中提出长查询用户满意度分析的整体框架,定义用户满意度的概念,并在用户日志中提取相关用户行为特征,应用决策树和SVM两种分类算法评测用户满意度.在大规模商业搜索引擎日志上完成的实验结果证明了这套评价体系的有效性.结果表明,用户对于查询满意和不满意的分类准确率分别达到86％和70％.     

A comparative study of information input devices for aging computer users

The fast aging of many western and eastern societies and their increasing reliance on information technology create a compelling need to reconsider older users' interactions with computers. Changes in perceptual and motor skill abilities that often accompany the aging process have important implications for the design of information input devices. This paper summarises the results of two comparative studies on information input with 90 subjects aged between 20 and 75 years. In the first study, three input devices – mouse, touch screen and eye-gaze control – were analysed concerning efficiency, effectiveness and subjective task difficulty with respect to the age group of the computer user. In the second study, an age-differentiated analysis of hybrid user interfaces for input confirmation was conducted combining eye-gaze control with additional input devices. Input confirmation was done with the space bar of a PC keyboard, speech input or a foot pedal. The results of the first study show that regardless of participants' age group, the best performance in terms of short execution time results from touch screen information input. This effect is even more pronounced for the elderly. Regarding the hybrid interfaces, the lowest mean execution time, error rate and task difficulty were found for the combination of eye-gaze control with the space bar. In conclusion, we recommend using direct input devices, particularly a touch screen, for the elderly. For user groups with severe motor impairments, we suggest eye-gaze information input.     

Online execution time prediction for computationally intensive applications with periodic progress updates

The effectiveness of distributed execution of computationally intensive applications (jobs) largely depends on the quality of the applied scheduling approach. However, most of the existing non-trivial scheduling algorithms rely on prior knowledge or on prediction of application parameters, such as execution time, size of input and output, dependencies, etc., to assign applications to the available computational resources. A major issue is that these parameters are hard to determine in advance, especially if the end user does not possess an extensive history of previous application runs. In this work we propose an online method for execution time prediction of applications, for which execution progress can be collected at run-time. Using dynamic progress information, the total job execution time can be predicted using extrapolation. However, the predictions achieved by extrapolation are far from precise and often vary over time as a result of changing application dynamics and varying resource load. Therefore, to compute the actual job execution time we match a number of predefined prediction evolution models against the consecutive extrapolations, by adopting nonlinear curve-fitting. The ??best-fit?? coefficients allow for more accurate execution time prediction. The predictions made are used to enhance a dynamic scheduling algorithm for workflows introduced in our earlier work. The scheduling algorithm is run with and without curve-fitting, showing a performance improvement of up to 15% in the former case.     

A Java/CORBA virtual machine architecture for remote execution of optimization solvers in heterogeneous networks

Virtual machines for remote execution are a useful tool for utilizing light user interfaces and intensive application cores in different physical machines connected through the Internet. In a virtual machine, application cores are distributed in a network. Specific locations, operating systems and hardware characteristics are hidden by virtual machines. They make it possible to use a PC to execute user interfaces and (a few) high‐performance computers for application cores. We present a Java/CORBA‐based brokerage platform that allows remote execution of optimization solvers from a client running on any platform. The system offers a dynamic library of available problem solvers, and a graphic interface to browse several defined properties and metadata on available solvers. In addition, an embedded file compression module to reduce data transfer time is included as a plug‐in feature of the proposed virtual machine. Analogous systems could be constructed for applications in which interaction traffic time is much lower than execution time. Copyright © 2001 John Wiley & Sons, Ltd.     

User-level failure detection and auto-recovery of parallel programs in HPC systems

As the mean-time-between-failures (MTBF) continues to decline with the increasing number of components on large-scale high performance computing (HPC) systems, program failures might occur during the execution period with high probability. Ensuring successful execution of the HPC programs has become an issue that the unprivileged users should be concerned. From the user perspective, if the program failure cannot be detected and handled in time, it would waste resources and delay the progress of program execution. Unfortunately, the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited privilege. Currently, automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are missing. This paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed jobs. The state checker in our method is encapsulated as an independent job to reduce interference with the user jobs. In addition, we propose a dual-checker mechanism to improve the robustness of our approach.We implement the proposed method as a tool named automatic re-launcher (ARL) and evaluate it on the Tianhe-2 system. Experiment results show that ARL can detect the execution failures effectively on Tianhe-2 system. In addition, the communication and performance overhead caused by ARL is negligible. The good scalability of ARL makes it applicable for large-scale HPC systems.     

Integrating PHIGS and User Interface Systems

The past five years has seen an explosion of rich and effective user interface management systems and toolkits and an increase in the expectations regarding application portability. Nearly a decade old, the PHIGS input model is inadequate in the face of this variety. "Fixing PHIGS" input would be a long and arduous task. Instead, PHIGS should be adapted to cooperate, not compete, with user interface systems. This can be done in two ways. An application can use both PHIGS input and input from a user interface system to accomplish its goals. Alternatively, an application can use input only from a user interface system, but in this case it needs utilities in PHIGS to gain access to information only PHIGS can supply. Specifically the utilities are needed for application-initiated picking and for coordinate mapping.     

An efficient hybrid similarity measure based on user interests for recommender systems

Recommender systems are used to suggest items to users based on their interests. They have been used widely in various domains, including online stores, web advertisements, and social networks. As part of their process, recommender systems use a set of similarity measurements that would assist in finding interesting items. Although many similarity measurements have been proposed in the literature, they have not concentrated on actual user interests. This paper proposes a new efficient hybrid similarity measure for recommender systems based on user interests. This similarity measure is a combination of two novel base similarity measurements: the user interest–user interest similarity measure and the user interest–item similarity measure. This hybrid similarity measure improves the existing work in three aspects. First, it improves the current recommender systems by using actual user interests. Second, it provides a comprehensive evaluation of an efficient solution to the cold start problem. Third, this similarity measure works well even when no corated items exist between two users. Our experiments show that our proposed similarity measure is efficient in terms of accuracy, execution time, and applicability. Specifically, our proposed similarity measure achieves a mean absolute error (MAE) as low as 0.42, with 64% applicability and an execution time as low as 0.03 s, whereas the existing similarity measures from the literature achieve an MAE of 0.88 at their best; these results demonstrate the superiority of our proposed similarity measure in terms of accuracy, as well as having a high applicability percentage and a very short execution time.     

Robot teleoperation environments featuring WAP-based wireless devices

This article describes the results of a pilot study investigating the feasibility of building teleoperation systems that use existing wireless infrastructure. In particular, it presents the design and implementation of a WAP-based system for mobile robot teleoperation. The system allows the operator to control the movement of a mobile robot equipped with a video camera through a mobile phone. The user periodically receives in the phone screen video frames from the robot camera that depict the camera input before and after the execution of a motion command by the robot. The article presents results of user trials with the system, describes the limitations of this approach and proposes ways of overcoming these limitations.     

Dynamic analysis of program performance (DAP) in a fortran batch environment

‘Frequency counts add an important new dimension to Fortran programs; indeed, it is difficult to express in words how “eye opening” they are’ (Knuth¹). Given a source program as input, a DAP environment effects changes to the execution of the program so that when the object code is run, the output of the program includes a list of the executable statements and their execution counts (a profile). By extending this basic principle so that the analysis also includes a time estimate for the statement (generated from the code associated with the statement) and a measure of the relative importance of the statement (with respect to the total run time of the object) the DAP report not only becomes an effective user software aid, but, also, an invaluable research tool. This paper discusses the development of such a DAP environment within a Fortran Batch System.     

基于LSTM的集群用户作业执行时间预测模型

为提升服务质量,数据中心需要确保在规定的截止时间前完成用户作业,因此必须根据实时的系统资源对作业进行有效的调度。提出了一种作业调度算法,根据预测的作业执行时间进行批作业调度,以最小化批作业的完成时间。作业执行时间预测模型基于长短期记忆LSTM网络,根据用户作业类型、作业量、作业需要的CPU核数和内存数量,以及作业需要的资源在系统总资源中的占比,对用户作业的执行时间进行预测。预测结果用于判断集群是否有能力按时完成用户作业,同时为合理安排各作业的执行顺序提供依据。通过实验确定了影响LSTM时间预测模型性能的各超参数取值,如迭代次数、学习率和网络层数等。实验表明,与SVR模型、ARIMA模型和BP模型相比,基于LSTM的作业执行时间预测模型的决定系数R2分别有2.97%,2.34%和5.66%的提升效果,且预测的平均误差仅为0.78%。     

Resource Management in a Distributed Computer System with Allowance for the Level of Trust to Computational Components

This article considers the ensuring of secure data processing in distributed computer systems (DCSs), which is important for a certain class of computing tasks. An approach to the resource management in DCSs is proposed that makes it possible to take into account, according to user requirements, both the time spent on the execution of a task and the security level of the system resources involved in its execution.