嵌入式自适应实时资源管理

现存的资源管理方法是针对传统的封闭嵌入实时系统设计的,在动态环境时难以保证系统的服务质量。为此,依据新一代典型动态实时系统的需求,运用基于控制论的自适应实时资源管理方法,改进Red Hat公司的eCos操作系统,在原eCos操作系统中加入基于控制论的实时调度架构、RM调度器、实时任务API和系统监视器,实现一个嵌入式自适应实时资源管理架构。实验结果证明,该架构具有更精确和高效的服务质量,保证系统实时动态的资源需求和实时任务的正确性。     

基于多维QoS的集群作业调度算法

调度技术是集群作业管理系统的关键技术之一。但是,目前大多数集群作业管理系统采用的调度技术,很少按照应用对系统资源的需求加以详细区分和权衡,无法同时满足不同应用在高吞吐量、高可用性和实时性等方面的要求,造成了资源的闲置和资源因为负载过重而无法正常工作。该文正是注意到了这种不足,根据不同应用的需求和实时收集到的资源信息,引入了多维QoS的概念,并给出了多维QoS的数学模型,提出了一种基于多维QoS的集群作业调度算法JSBMQ,充分提高了系统的资源利用率和平均响应时间,使集群可以提供不问断的高效的计算服务。     

HeiRAT - Quality-of-service management for distributed multimedia systems

Multimedia systems must be able to support a certain quality of service (QoS) to satisfy the stringent real-time performance requirements of their applications. HeiRAT, the Heidelberg Resource Administration Technique, is a comprehensive QoS management system that was designed and implemented in connection with a distributed multimedia platform for networked PCs and workstations. HeiRAT includes techniques for QoS negotiation, QoS calculation, resource reservation, and resource scheduling for local and network resources.     

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。     

一种基于标准化QoS公平的反馈控制实时调度算法

任务间的QoS公平性是多QoS级别的可调节动态实时调度系统中的一个重要问题.本文引入了标准化QoS公平的概念,在公平性中加入了任务的重要性因素,并构造了具有PID反馈控制环节的实时调度算法NF-QoS来达到标准化QoS公平.利用NF-QoS对系统截止期错失率进行实时采样,定期反馈给PID控制器,根据PID控制器计算的结果对各任务QoS级别进行调整,以保证各任务公平地得到处理器资源.实验结果表明,NF-QoS不仅合理地协调了系统利用率和截止期错失率,并且有效地提高了系统的QoS公平性.     

RTAI下动态集成的资源预留调度器的设计与实现

近年来基于双内核架构增强Linux操作系统实时性的RTAI(Real-Time Application Interface)在工业控制等硬实时领域得到广泛应用。RTAI通过抢占Linux的执行来保障硬实时性,Linux被抢占的时间依赖于硬实时应用的处理器要求而每次均会有较大不同,导致Linux的执行时间不可预测,从而无法保障软实时应用的服务质量。动态集成的资源预留调度器(Dynamic Integrated Resource Reserved Scheduler,DIRRS)通过增强RTAI调度器使其支持资源预留机制,在Linux实现可动态集成的、基于服务器的调度策略,不但可以保证Linux及其以上的软实时应用,即使在有硬实时任务并发时也能得到处理器资源,而且很容易通过更换不同的服务器内核模块来实现用户自定义的调度策略。     

Integrated QoS-aware resource management and scheduling with multi-resource constraints

In dynamic real-time systems such as sensor networks, mobile ad hoc networking and autonomous systems, the mapping between level of service and resource requirements is often not fixed. Instead, the mapping depends on a combination of level of service and outside environmental factors over which the application has no direct control. An example of an application where environmental factors play a significant role is radar tracking. In radar systems, resources must be shared by a set of radar tasks including tracking, searching and target confirmation tasks. Environmental factors such as noise, heating constraints of the radar and the speed, distance and maneuverability of tracked targets dynamically affect the mapping between the level of service and resource requirements. The QoS manager in a radar system must be adaptive, responding to dynamic changes in the environment by efficiently reallocating resource to maintain an acceptable level of service. In this paper, we present an integrated QoS optimization and dwell scheduling scheme for a radar tracking application. QoS optimization is performed using the Q-RAM (Baugh, 1973, ghosh-et al.,2004a approach. Heuristics are used to achieve a two order magnitude of reduction in optimization time over the basic Q-RAM approach allowing QoS optimization and scheduling of a 100 task radar problem to be performed in as little as 700 ms with only a 0.1% QoS penality over Q-RAM alone. Sourav Ghosh received the B.Tech degree in Electronics and Electrical Communications Engineering from Indian Institute of Technology, Kharagpur, India, in 1997, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA, USA, in 1999 and 2004 respectively. He is currently working as a Technical Staff at Oracle in Cluster Database Group (RAC). His research interest includes OS resource management and scheduling, performance analysis, Quality of Service (QoS) and real-time systems.     

非周期软实时系统的动态最优控制方法

运用多优先级排队系统的分析方法,研究了到达时刻和执行时间均不确定的非周期软实时系统,提出了一种针对DM调度算法的动态最优控制方法。该方法能在统计意义上确保系统的实时性,同时又兼顾系统的QoS需求和提高系统吞吐率。实例表明，该方法能提高系统的实际利用率，降低系统的截止时间错过率,是一种有效的载荷管理方法。     

A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE

Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service (QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.      

Hierarchical control of multiple resources in distributed real-time and embedded systems

Real-time and embedded systems have traditionally been designed for closed environments where operating conditions, input workloads, and resource availability are known a priori, and are subject to little or no change at runtime. There is increasing demand, however, for adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. A challenging problem faced by researchers and developers of such systems is devising effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements of applications. To address key resource management challenges of open DRE systems, this paper presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which provides adaptive resource management using control techniques that adapt to workload fluctuations and resource availability for both bandwidth and processor utilization simultaneously. This paper presents three contributions to research in adaptive resource management for DRE systems. First, we describe the structure and functionality of HiDRA. Second, we present an analytical model of HiDRA that formalizes its control-theoretic behavior and presents analytical assurance of system performance. Third, we evaluate the performance of HiDRA via experiments on a representative DRE system that performs real-time distributed target tracking. Our analytical and empirical results indicate that HiDRA yields predictable, stable, and efficient system performance, even in the face of changing workload and resource availability.     

Integrated Adaptive QoS Management in Middleware: A Case Study

Distributed real-time and embedded (DRE) systems in which application requirements and environmental conditions may not be known a priori—or which may vary at run-time—can benefit from an adaptive approach to management of quality-of-service (QoS) to meet key constraints, such as end-to-end timeliness. Moreover, coordinated management of multiple QoS capabilities across multiple layers of applications and their supporting middleware can help to achieve necessary assurances of meeting these constraints.This paper offers two contributions to the study of adaptive DRE computing systems: (1) a case study of our integration of multiple middleware QoS management technologies to manage quality and timeliness of imagery adaptively within a representative DRE avionics system and (2) empirical results and analysis of the impact of that integration on key trade-offs between timeliness and image quality in that system.This work was supported in part by AFRL contract F33615-97-D-1155/0005 (WSOA), NSF ITR CCR-0312859, Siemens, and DARPA/AFRL contracts F33615-03-C-4112, F30602-98-C-0187 and F33615-00-C-1694. Approved for public release, distribution unlimited.Christopher D. Gill is an Assistant Professor in the Department of Computer Science and Engineering at Washington University in St. Louis. He has published over 50 refereed technical articles in leading journals, conferences, workshops, and book series. His research focuses on distributed real-time embedded systems, with particular emphasis on adaptive mresource management, scheduling, and software design and implementation for time-and-space constrained systems. Dr. Gill has chaired numerous workshop and conference program committees, and has participated widely in review panels and standards organizations in the distributed and real-time systems areas. The research he has led has produced several freely available open-source software frameworks including the Kokyu scheduling and dispatching framework and the nORB small-footprint real-time object request broker.Jeanna Gossett joined The Boeing Company in 1999 as a member of Bold Stroke/Open Systems Architecture team. Jeanna has worked on several CRAD projects including Weapon Systems Open Architecture (WSOA) where she was responsible for incorporating quality of service and resource management software technology into the fighter aircraft real-time embedded system application. Jeanna has since joined the F/A-18 New Product Development Mission Systems team. Prior to joining The Boeing Company in 1999, she worked in the telecommunications industry as an embedded systems developer at Ericsson and Siemens AG. Jeanna received a B.S. in Electrical Engineering from Southern Illinois University, Edwardsville and is a 2005 M.B.A. candidate at Washington University in St. Louis.David Corman is a Technical Fellow at the Boeing Company, located in St. Louis, Mo. Dave is the chief scientist for the Network Centric Operations (NCO) thrust in Phantom Works (PW) and is responsible for developing the NCO technology research agenda and investment strategy. He is also the Principle Investigator (PI) for a variety of Air Force and Defense Advanced Research Project Agency (DARPA) programs that are producing technologies for integrating legacy platforms into the emerging Global Information Grid and for autonomous control of unmanned systems. Since joining the former McDonnell-Douglas (now part of the Boeing Company) in 1983, Dave has worked on numerous projects ranging from embedded systems to large C4I and weapon systems. A major focus of Daves career has been on the development of C4I system simulations and in mission planning system development for aircraft and missiles. He has also served as a consultant to many weapon system and C4I programs in St. Louis, Seattle, and California. Prior to joining McDonnell-Douglas, Dave spent five years at the Johns Hopkins University Applied Physics Laboratory. He was the first recipient of a Naval Research Laboratory Fellowship from the University of Maryland—College Park where he received his PhD in Electrical Engineering in 1983.Joseph Loyall is a division scientist at BBN Technologies, where he leads the Distributed Real-time Embedded (DRE) systems research thrust in the Distributed Systems Advanced Middleware Technology group. He is actively involved in developing integrated dynamic resource management capabilities and advanced software engineering using model driven architecture (MDA) approaches, and in applying adaptive behavior to operational embedded systems such as collections of unmanned and manned air vehicles. Dr. Loyall has a Ph.D. and M.S. in computer science from the University of Illinois and a B.S. in computer science from Indiana University. He can be contacted at jloyall@bbn.com.Richard E. Schantz is a principal scientist at BBN Technologies in Cambridge, Mass., where he has been a key contributor to advanced distributed computing R&D for the past 30 years. His research has been instrumental in defining and evolving the concepts underlying middleware since its emergence in the early days of the Internet. He was directly responsible for developing the first operational distributed object computing capability and transitioning it to production use. More recently, he has led research efforts toward developing and demonstrating the effectiveness of middleware support for adaptively managed Quality Of Service control, as principal investigator on a number of key DARPA projects in the areas of adaptive real-time behavior, survivability and advanced software engineering. Schantz received his Ph.D. degree in Computer Science from the State University of New York at Stony Brook, in 1974.Michael Atighetchi is a senior scientist at BBN Technologies and a senior member of the Distributed Systems Advanced Middleware Technology group. His interests include use of adaptation in survivable systems, network and operating system security, and distributed coordination. Contact him at matighet@bbn. comDouglas C. Schmidt (d.schmidt@vanderbilt.edu) is a Professor of Electrical Engineering and Computer Science, Associate Chair of the Computer Science and Engineering program, and a Senior Researcher in the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has published over 300 technical papers and books that cover a range of research topics, including patterns, optimization techniques, and empirical analyses of software frameworks and domain-specific modeling environments that facilitate the development of distributed real-time and embedded (DRE) middleware and applications running over high-speed networks and embedded system interconnects. Dr. Schmidt has served as a Deputy Office Director and a Program Manager at DARPA, where he led the national R&D effort on middleware for DRE systems.     

Managing deadline miss ratio and sensor data freshness in real-time databases

The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. We define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns.     

实时多任务过程控制机软件设计

本文从实用角度论述了一种可用于分布式系统和用户控制任务相对独立环境的实时多任务过程控制软件的整体设计思想、软件结构和实现的一般方法。文中还分别给出了两级系统监控级和过程控制级软件的实例。     

基于跨层的中高速传感器网络多元参数调度与资源自适应分配算法

针对中高速传感器网络中不同业务对QoS(quality of scrvice)的不同要求,跨层考虑物理层和数据链路层参数,提出了一种适合混合业务的多元参数调度算法和资源分配算法。该算法根据不同的业务动态调整时延补偿因子和吞吐量补偿因子两个参数,在满足实时业务QoS约束的前提下,以最大化系统吞吐量为目标建立了相应的优化模模型,对于实时业务能满足时延较小的要求,对于非实时业务能满足吞吐量较大的要求。仿真结果表明,该调度算法可以灵活地在系统功率效率和用户服务质量满意度之间取得折衷,并保证不同类型业务用户间的公平性。     

实时多核嵌入式系统研究综述

随着计算机系统与物理世界的结合越来越紧密,实时系统需要承担越来越复杂的运算任务.多核处理器的兴起为同时满足实时性约束和高性能这两方面的需求提供了可能.基于多核处理器的实时嵌入式系统的研究已成为近几年研究的热点.对现有的面向实时多核嵌入式系统的研究工作进行了综述,介绍了实时多核嵌入式系统的关键设计问题,从多核共享资源干扰及管理、多核实时调度、多核实时程序并行化、多核虚拟化技术、多核能耗管理和优化等几个方面对现有研究工作进行了分析和总结,并展望了实时多核系统领域进一步的研究方向.     

AQuoSA—adaptive quality of service architecture

This paper presents an architecture for quality of service (QoS) control of time‐sensitive applications in multi‐programmed embedded systems. In such systems, tasks must receive appropriate timeliness guarantees from the operating system independently from one another; otherwise, the QoS experienced by the users may decrease. Moreover, fluctuations in time of the workloads make a static partitioning of the central processing unit (CPU) that is neither appropriate nor convenient, whereas an adaptive allocation based on an on‐line monitoring of the application behaviour leads to an optimum design. By combining a resource reservation scheduler and a feedback‐based mechanism, we allow applications to meet their QoS requirements with the minimum possible impact on CPU occupation. We implemented the framework in AQuoSA (Adaptive Quality of Service Architecture (AQuoSA). http://aquosa.sourceforge.net ), a software architecture that runs on top of the Linux kernel. We provide extensive experimental validation of our results and offer an evaluation of the introduced overhead, which is perfectly sustainable in the class of addressed applications. Copyright © 2008 John Wiley & Sons, Ltd.     

Parallel Concurrency Control Activity for Transaction Management in Real-time Database Systems

In a real-time database system, an application supports a mix of transactions. These include the real-time transactions that require completion by a given deadline. Time-critical requirements also exist in many distributed multi-media system applications. Existing concurrency control procedures introduce excessive delays due to non-availability of data resources. In this study, we ignore the delays incurred by ordinary transactions, in order to achieve a non-interference mode of execution (near parallel) for the time-critical transactions. For this purpose, a data allocation model has been studied. It is a stochastic process model based on the use of two-phase locking. It highlights the available possibilities for reductions of delays for time-critical transactions within a distributed real-time database systems. Based on the new conceptual model, modified synchronization techniques for time-critical transactions have been proposed.     

基于中间件的实时内存调度

在数据密集型实时监测系统中，任务需要通过分配内存来存储和处理动态变化的信息。该文提出了一种基于中间件的新型内存调度器，通过反馈驱动来调节实时任务的内存分配，与受控任务保持平滑的连接，开放结构允许系统设计人员增加或修改内存管理策略。测试结果表明，内存调度器引起的开销较小，能有效地协调资源共享冲突。