嵌入式分布实时系统自适应资源管理架构

分析了开放嵌入式分布实时(Distributed Real-time and Embedded,DRE)系统的自适应资源管理需求,针对传统静态资源管理方法的不足,提出了一种面向开放DRE系统的自适应资源管理架构;该架构采用动态任务管理、实时资源分配和自适应控制三种关键技术,能够更加适用于开放、动态的环境,有效应对资源约束和资源状态、应用程序QoS的变化;提高系统性能和稳定性;屏蔽底层硬件资源的异构性,为上层应用提供统一的服务接口。     

Trade-Off Analysis of Real-Time Control Performance and Schedulability*

Most real-time computer-controlled systems are developed in two separate stages: controller design followed by its digital implementation. Computational tasks that implement the control algorithms are usually scheduled by treating their execution times and periods as unchangeable parameters. Task schedulability therefore depends only on the limited computing resources available. On the other hand, controller design is primarily based on the continuous-time dynamics of the physical system being controlled. The set of tasks resulting from this controller design may not be schedulable with the limited computing resources available. Even if the given set of tasks is schedulable, their overall performance may not be optimal in the sense that they do not make a full use of the computing resources. In this paper, we propose an integrated approach to controller design and task scheduling. Specifically, task frequencies (or periods) are allowed to vary within a certain range as long as such changes do not affect critical control functions such as the maintenance of system stability. We present an algorithm that determines the task frequencies such that a prescribed aspect of system performance is optimized subject to satisfaction of computing resource constraints. The tasks are then scheduled with the chosen frequencies. The proposed approach also addresses the issue of choosing controller processors.     

资源预留调度算法在虚拟化环境中的设计与实现

虚拟化技术在服务器领域已经得到广泛应用,可以在一台服务器或服务器集群上同时运行几个不同的操作系统,诸多优点包括:故障隔离、高效利用资源、负载均衡、安全性等.常用的虚拟化系统如VMware、Virtual PC等采用全虚拟化技术,比较消耗资源,因此不适用于嵌入式领域的应用.而Xen采用半虚拟化技术,性能方面得到了很大提升,为虚拟化技术在嵌入式领域的应用创造了条件.由于嵌入式设备有着数据实时采集、现场控制、高危环境等特殊应用背景,嵌入式系统对实时性都有一定的要求.目前的虚拟化技术没有很好的方法来保障系统的实时性.本文在XEN虚拟化环境中设计并实现基于资源预留的实时调度算法,即在虚拟机监视器(Virtual Machine Monitor,VMM)层面实现常量带宽服务器(Constant Bandwidth Server,CBS)调度算法,用于有效调度实时和非实时的虚拟机子系统,并保障不同子系统之间的性能隔离.     

基于概率的实时任务调度分析

在某些软实时系统中,为了降低系统成本,允许系统过载,并且允许过载时少量任务能错失时限;对于这样的系统,常常能设法获得其任务的执行时间所服从的概率分布。针对这样的系统,提出了基于概率的可调度分析方法,对系统的性能作出概率上的估计,在概率意义上预测系统的可行性;并提出以数据挖掘技术估算任务执行时间的分类方法,这对预测系统的性能和提高系统利用率有重要的意义。     

基于服务质量(QoS-Based)的ASOS资源分配与调度研究

论文针对嵌入式实时操作系统的特性提出了一种基于服务质量的ASOS系统资源管理、任务调度的模型框架,以该框架为基础,采用模糊反馈控制算法实现了对智能交通路口控制器的软件设计和具体实现。     

A DVS-assisted hard real-time I/O device scheduling algorithm

The I/O subsystem has become a major source of energy consumption in a hard real-time monitoring and control system. To reduce its energy consumption without missing deadlines, a dynamic power management (DPM) policy must carefully consider the power parameters of a device, such as its break-even time and wake-up latency, when switching off idle devices. This problem becomes extremely complicated when dynamic voltage scaling (DVS) is applied to change the execution time of a task. In this paper, we present COLORS, a composite low-power scheduling framework that includes DVS in a DPM policy to maximize the energy reduction on the I/O subsystem. COLORS dynamically predicts the earliest-access time of a device and switches off idle devices. It makes use of both static and dynamic slack time to extend the execution time of a task by DVS, in order to create additional switch-off opportunities. Task workloads, processor profiles, and device characteristics all impact the performance of a low-power real-time algorithm. We also identify a key metric that primarily determines its performance. The experimental results show that, compared with previous work, COLORS achieves additional energy reduction up to 20%, due to the efficient utilization of slack time.

Resource Management Middleware for Dynamic,Dependable Real-Time Systems

Thispaper presents resource management techniques that achieve thequality of service (QoS) requirements of dynamic real-time systemsusing open architectures and commercial off-the-shelf technologies(COTS). Dynamic real-time systems are subject to constant changessuch as a varying external environment, overload of internalsystems, component failure, and evolving operational requirements.Examples of such systems include the emerging generation of computer-based,command and control systems of the U.S. Navy. To enable the engineeringof such systems, we present adaptive resource management middlewaretechniques that achieve the QoS requirements of the system. Themiddleware performs QoS monitoring and failure detection, QoSdiagnosis, and reallocation of resources to adapt the systemto achieve acceptable levels of QoS. Experimental characterizationsof the middleware using a real-time benchmark illustrate itseffectiveness for adapting the system for achieving the desiredreal-time and survivability QoS during overload situations.     

检修公司人事劳资管理系统

检修公司人事劳资管理系统是典型的管理信息系统(MIS),本系统所创建的模块实现了如下功能:基本信息管理模块包含部门信息管理模块和员工信息管理模块,可以实现部门信息和员工信息的增加、删除、修改、查看功能;考勤考评管理模块可以实现记录的创建、修改、删除、查看功能;员工工资管理模块可以实现对员工的基本工资进行设定,对奖金以及福利补贴进行设置,用户可根据当月的情况对实发工资计算公式进行调整,根据出勤统计结果来计算本月各项实际金额以及对统计出的工资进行浏览;系统用户管理模块可以实现对普通用户的创建、密码复位、删除用户、修改自身密码,并且实现了用户的分权限管理,系统管理员具有操作本系统的所有权限,而普通用户只具有浏览权限;日志管理模块具有操作日志功能,普通用户只能浏览日志信息,管理员用户既可以浏览,又可以清空操作日志记录。     

一种动态自适应的计算网格资源管理方法

提出了资源组的原子性分配,保证了同一作业相关资源的协同分配,并避免了资源申请的死锁问题和资源昀无效占用。首先,给出了网格资源管理框架;然后提出了资源分配方法的数学模型,并引入了资源分配求解的近似算法。     

基于绩效管理的人力资源管理分析

随着社会经济的不断发展,企业的生存发展越来越离不开人力资源管理。人力资源的发掘、培养以及之后的人力资源绩效考核已经成为每个企业的工作重点。绩效管理有利于提高企业的经济效益,也是激励员工的重要手段。     

嵌入式软件跟踪调试技术的研究与设计

针对在嵌入式实时操作系统环境下高低优先级任务切换过程引起的跟踪信息乱序和丢失问题,对跟踪信息嵌套缓存机制和解析机制进行了设计,提出了物理缓存管理机制与递归调用解析机制相结合、备份缓存管理机制与普通查询解析机制相结合的两种跟踪方案,解决了跟踪信息乱序和丢失问题,提高了跟踪系统的运行效率。     

基于反馈控制理论的流媒体服务器资源管理模型

如何合理地分配系统资源，使流媒体服务器能够在满足客户基本QoS的前提下，支持尽可能多的并发服务，是流媒体研究领域的重要组成部分．提出了基于反馈控制理论的流媒体服务器资源调度模型及核心调度算法．该模型通过周期地采集系统的工作状态，并以此为根据调整任务在下一个采样周期内的运行属性，达到在满足任务的QoS的前提下，提高系统的并发程度的目的．详细分析了模型结构和核心算法的实现机制，并利用模拟平台对该算法进行了性能分析．     

Using Markets to Engineer Resource Management for the Information Grid

Information systems are continually expanding as evidenced by the doubling of Internet connections every year. Similar growth is exhibited by information systems in defense. The Air Force's goals to achieve global awareness, dynamic planning/execution, and global information exchange involve the technologies to provide information to the warrior anywhere, anytime, and for any mission. This far-reaching enterprise will necessarily span multiple networks and computing domains of both the commercial and military varieties. As a result, many users with different goals and priorities vie for the communication and computing resources of the information grid. Managing this vast system to assure dependable operation that maintains users' quality of service levels has led researchers to propose economic models to solve the resource management problem. Information technology has begun to fundamentally alter the way business is conducted, and there is synergy between e-commerce and the management of the underlying information resources on which it runs.This paper examines the envisioned market-based, large-scale information systems for defense. Due to their criticality, these systems must also manage resources to provide survivability in the presence of information attacks. This potential for technology transfer from the defense sector to the commercial sector are described. Conversely, the leveraging of research performed in the non-military realm of e-commerce to reach the Air Force's goals will also be explored.     

Dynamic buffer management using optimal control of hybrid systems

This paper studies a dynamic buffer management problem with one buffer inserted between two interacting components. The component to be controlled is assumed to have multiple power modes corresponding to different data processing rates. The overall system is modeled as a hybrid system and the buffer management problem is formulated as an optimal control problem. Different from many previous studies, the objective function of the proposed problem depends on the switching cost and the size of the continuous state space, making its solution much more challenging. By exploiting some particular features of the problem, the best mode sequence and the optimal switching instants are characterized analytically using a variational approach. Simulation results based on real data shows that the proposed method can significantly reduce the energy consumption compared with another heuristic scheme in several typical situations.     

Approximation algorithm for periodic real-time tasks with workload-dependent running-time functions

This paper addresses the problem of resource allocation for distributed real-time periodic tasks, operating in environments that undergo unpredictable changes and that defy the specification of meaningful worst-case execution times. These tasks are supplied by input data originating from various environmental workload sources. Rather than using worst-case execution times (WCETs) to describe the CPU usage of the tasks, we assume here that execution profiles are given to describe the running time of the tasks in terms of the size of the input data of each workload source. The objective of resource allocation is to produce an initial allocation that is robust against fluctuations in the environmental parameters. We try to maximize the input size (workload) that can be handled by the system, and hence to delay possible (costly) reallocations as long as possible. We present an approximation algorithm based on first-fit and binary search that we call FFBS. As we show here, the first-fit algorithm produces solutions that are often close to optimal. In particular, we show analytically that FFBS is guaranteed to produce a solution that is at least 41% of optimal, asymptotically, under certain reasonable restrictions on the running times of tasks in the system. Moreover, we show that if at most 12% of the system utilization is consumed by input independent tasks (e.g., constant time tasks), then FFBS is guaranteed to produce a solution that is at least 33% of optimal, asymptotically. Moreover, we present simulations to compare FFBS approximation algorithm with a set of standard (local search) heuristics such as hill-climbing, simulated annealing, and random search. The results suggest that FFBS, in combination with other local improvement strategies, may be a reasonable approach for resource allocation in dynamic real-time systems. David Juedes is a tenured associate professor and assistant chair for computer science in the School of Electrical Engineering and Computer Science at Ohio University. Dr. Juedes received his Ph.D. in Computer Science from Iowa State University in 1994, and his main research interests are algorithm design and analysis, the theory of computation, algorithms for real-time systems, and bioinformatics. Dr. Juedes has published numerous conference and journal papers and has acted as a referee for IEEE Transactions on Computers, Algorithmica, SIAM Journal on Computing, Theoretical Computer Science, Information and Computation, Information Processing Letters, and other conferences and journals. Dazhang Gu is a software architect and researcher at Pegasus Technologies (NeuCo), Inc. He received his Ph.D. in Electrical Engineering and Computer Science from Ohio University in 2005. His main research interests are real-time systems, distributed systems, and resource optimization. He has published conference and journal papers on these subjects and has refereed for the Journal of Real-Time Systems, IEEE Transactions on Computers, and IEEE Transactions on Parallel and Distributed Systems among others. He also served as a session chair and publications chair for several conferences. Frank Drews is an Assistant Professor of Electical Engineering and Computer Science at Ohio Unversity. Dr. Drews received his Ph.D. in Computer Science from the Clausthal Unversity of Technolgy in Germany in 2002. His main research interests are resource management for operating systems and real-time systems, and bioinformatics. Dr. Drews has numerous publications in conferences and journals and has served as a reviewer for IEEE Transactions on Computers, the Journal of Systems and Software, and other conferences and Journals. He was Publication Chair for the OCCBIO’06 conference, Guest Editor of a Special Issue of the Journal of Systems and Software on “Dynamic Resource Management for Distributed Real-Time Systems”, organizer of special tracks at the IEEE IPDPS WPDRTS workshops in 2005 and 2006. Klaus Ecker received his Ph.D. in Theoretical Physics from the University of Graz, Austria, and his Dr. habil. in Computer Science from the University of Bonn. Since 1978 he is professor in the Department of Computer Science at the Clausthal University of Technology, Germany, and since 2005 he is visiting professor at the Ohio University. His research interests are parallel processing and theory of scheduling, especially in real time systems, and bioinformatics. Prof. Ecker published widely in the above mentioned areas in well reputed journals and proceedings of international conferences as well. He is also the author of two monographs on scheduling theory. Since 1981 he is organizing annually international workshops on parallel processing. He is associate editor of Real Time Systems, and member of the German Gesellschaft fuer Informatik (GI) and of the Association for Computing Machinery (ACM). Lonnie R. Welch received a Ph.D. in Computer and Information Science from the Ohio State University. Currently, he is the Stuckey Professor of Electrical Engineering and Computer Science at Ohio University. Dr. Welch performs research in the areas of real-time systems, distributed computing and bioinformatics. His research has been sponsored by the Defense Advanced Research Projects Agency, the Navy, NASA, the National Science Foundation and the Army. Dr. Welch has twenty years of research experience in the area of high performance computing. In his graduate work at Ohio State University, he developed a high performance 3-D graphics rendering algorithm, and he invented a parallel virtual machine for object-oriented software. For the past 15 years his research has focused on middleware and optimization algorithms for high performance computing. His research has produced three successive generations of adaptive resource management (RM) middleware for high performance real-time systems. The project has resulted in two patents and more than 150 publications. Professor Welch also collaborates on diabetes research with faculty at Edison Biotechnology Institute and on genomics research with faculty in the Department of Environmental and Plant Biology at Ohio University. Dr. Welch is a member of the editorial boards of IEEE Transactions on Computers, The Journal of Scalable Computing: Practice and Experience, and The International Journal of Computers and Applications. He is also the founder of the International Workshop on Parallel and Distributed Real-time Systems and of the Ohio Collaborative Conference on Bioinformatics. Silke Schomann graduated in 2003 with a M.Sc. in Computer Science from Clausthal University Of Technology, where she has been working as a scientific assistant since then. She is currently working on her Ph.D. thesis in computer science at the same university.     

嵌入式操作系统RTX51 Tiny的分析及应用

在嵌入式开发中,嵌入式操作系统的应用是重要的一环。文中对一种适用51单片机的实时多任务操作系统———RTX51 Tiny进行应用。首先从任务管理和内存管理的角度来分析该操作系统,在此基础上,用C语言编写应用程序traf-fic。应用实践得到以下结论:该操作系统的应用程序启动简单,没有操作系统的启动过程;短小精悍,代码不足50行;运行可靠,仿真、硬件运行结果充分证实了这一点。从而得到RTX51 Tiny操作系统对任务和堆栈管理的有效性及其代码精简和运行可靠的基本特点。     

人力资源管理信息系统设计分析

人力资源管理是企业管理十分重要的工作,在企业管理过程中,人力资源管理的信息化水平将在很大程度上影响到企业的经济利益,越来越受到社会的高度重视。首先介绍了人力资源管理信息系统的设计需求分析,并对该系统所涉及的人事管理子系统、招聘与选拔子系统、绩效评估子系统、薪酬管理子系统和培训管理子系统的总体设计及其性能要求进行了详细论述。     

嵌入式实时软件通用框架模型研究

框架是一种在某个领域获得软件重用的重要途径,描绘的是一个待建应用系统软件的主要结构.从实时嵌入式系统的两大特性着手,提出了一个通用的嵌入式实时软件框架模型,深入分析了该框架下的资源模型、时间模型、任务模型、调度模型和通信模型以及它们之间的相互依赖关系,并且进行了建模.该模型在某航空机载系统研究中得到了应用并切实提高了软件的开发效率和可维护性,具有一定的工程理论和应用价值.     

单调速率调度算法的可调度性分析与仿真

单调速率调度算法是一种经典的周期任务调度算法,在采用单调速率调度算法调度周期任务前对算法的可调度性进行分析和仿真是十分必要的。该文介绍了单调速率调度算法的基本调度规则和可调度的充分必要条件,分别基于Windows平台的多线程机制和实时操作系统SACOS的RMS管理器对单调速率调度算法的可调度性进行仿真,并对仿真结：果进行了评价与分析。仿真结果表明,这两种方法可为单调速率调度算法的可调度性分析提供有益的指导。