CORBA中间件在分布式飞行控制中的应用

针对无人直升机可重配分布式控制对软件平台的要求，借鉴操作系统与应用软件之间的中间件技术，利用实时CORBA的ORB技术、虚拟资源网和实时事件服务机制构建无人直升机分布式控制系统软件平台。虚拟资源网可使控制组件网络化，每个组件有唯一地址，网络中的其它资源不需要知道它的确切位置，只根据网络资源名就可以访问它。实时事件服务可使各控制组件快速、有效地通信，并且使组件设计时结构解耦，事件通道在事件提供者和事件消费者之间建立中介，有利于系统硬件的改进及软件组件的重配。应用仿真实例说明这种软件平台能有效、方便、快捷地实现分布式控制系统。     

一个分布式实时指挥监视系统

文中介绍一个基于Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒｅ模式的地分布式的一个实用的分布实时数据处理系统，该系统采用了Ｃｌｉｅｎｔ／Ｓｅｒｖｅｒ模式分布系统构造方法和ＷｉｎｄｏｗｓＮＴ提供的多线程抢先式多任务管理方式，引入带优先级的调用策及面向对象的编程技术，从而获得了较好的模块性和实时性。     

基于DRTSADL的分布式实时系统建模

在考察现有的体系结构描述语言的基础上,提出了一种新的分布式实时系统体系结构描述语言（DRTSADL）,研究了该语言操作语义。结合一个分布式实时前端系统实例描述,说明了DRTSADL的应用。与现存ADL相比,新的ADL对分布式实时系统有较强的描述能力。     

实现分布式仿真系统同步的一种方法

分布式仿真系统的构建过程中,关于各仿真子节点的协调运行与同步问题是其中的重点和难点。该文介绍了面向对象的实时仿真软件开发环境Constellation和网络传输服务NDDS这两个工具,并且结合这它们的特点和相互之间的密切联系,研究出一种应用它们实现分布式仿真系统同步的方法。最后建立一个卫星姿态控制仿真系统,介绍了如何实现这种方法,并且进行以下验证：在Constellation下和在Matlab下建立的仿真系统进行比较,验证系统和集中式系统仿真结果比较,验证系统在Windows操作系统下和实时操作系统下仿真结果比较。     

基于CORBA的分布式系统实时语音播放程序设计

随着计算机技术的发展出现了分布式系统应用,而如何在具有异构节点的环境中搭建分布式系统是其开发过程中的一个难点。本文介绍了CORBA技术,探究了CORBA的实时性,并在此基础上使用CORBA中间件在异构环境中搭建了分布式系统。此外,还通过CORBA实现了语音数据的实时传递及播放,并在实际环境中对程序进行了测试。测试结果表...     

网络环境下虚拟机器人——“SoftMan”系统平台总体设计

基于网络环境虚拟机器人的计算模式融合分布式人工智能、并行分布式系统、移动智体和人工生命的技术,是计算机网络时代的一项崭新而关键技术,不仅会实现更灵活的分布式异步计算,而且将把网络计算带入一个全新的智能化时代。这种计算方式在如何充分利用网络资源,如何给移动用户提供高效的服务等诸多问题上提供了新的思路,目前主要研究领域集中在动态信息获取、智能网络、电子商务、主动网络和移动智能通信网络等。本文系统阐述“SoftMan”系统平台的设计方法、开发策略、总体架构和软件实现,同时对其相关支撑技术进行了剖析;最后就“Soft—Man”系统开发的思路和未来研究趋势进行了展望。     

Comparative analysis of two different middleware approaches for reconfiguration of distributed real-time systems

Software-based reconfiguration of distributed real-time systems is a complex problem with many sides to it ranging from system-wide concerns down to the intrinsic non-robust nature of the specific middleware layer and the used programming techniques. In a completely open distributed system, mixing reconfiguration and real-time is not possible; the set of possible target states can be very large threatening the temporal predictability of the reconfiguration process. Over the last years, middle ware solutions have appeared mainly for general purpose systems where efficient state transitions are sought for, but real-time properties are not considered. One of the few contributions to run-time software reconfiguration in distributed real-time environments has been the iLAND middleware, where the germ of a solution with high potential has been conceived and delivered in practice.¹ The key idea has been the fact that a set of bounds and limitations to the structure of systems and to their open nature needs to be imposed in order to come up with practical solutions. In this paper, the authors present the different sides of the problem of software reconfiguration from two complementary middleware perspectives comparing two strategies built inside distribution middleware. We highlight the lessons learned in the iLAND project aimed at service-based reconfiguration and compare it to our experience in the development of distributed real-time Java reconfiguration based on distributed tasks rescheduling. Authors also provide a language view of both solutions. Lastly, empirical results are shown that validate these solutions and compare them on the basis of different programming language realizations.     

Integration framework for intelligent manufacturing processes

In this article, we describe a new approach to applying distributed artificial intelligence techniques to manufacturing processes. The construction of intelligent systems is one of the most important techniques among artificial intelligence research. Our goal is to develop an integrated intelligent system for real time manufacturing processes. An integrated intelligent system is a large knowledge integration environment that consists of several symbolic reasoning systems (expert systems) and numerical computation packages. These software programs are controlled by a meta-system which manages the selection, operation and communication of these programs. A meta-system can be implemented in different language environments and applied to many disciplines. This new architecture can serve as a universal configuration to develop high performance intelligent systems for many complicated industrial applications in real world domains.To whom all correspondence should be addressed.     

Low complexity reconfiguration for real-time data-intensive service-oriented applications

Next generation distributed real-time systems will be complex high-performance environments containing applications with a flexible structure, integrating a large number of nodes of heterogeneous nature characterized by multiple and decoupled software units scattered all over the distributed environment; they are expected to offer data-intensive capabilities through merging the processing power of large numbers of nodes. These systems will have increased dynamic behavior by suffering frequent reconfigurations or state transitions resulting, among others, from the changing nature of the processed data. Handling the dynamics of these systems in real-time is a complex problem that requires to impose some bounds to the structure of the system to really achieve timely response not only during normal operation but also in the event of reconfigurations. In this paper, we present an approach to achieve real-time reconfiguration in distributed real-time service-based systems modeled as graphs. A reconfiguration requires to search for a new schedulable/valid solution or state from a complete system graph that contains all tentative solutions; each of these solutions will have undergo a schedulability analysis to determine if it is a valid solution; if the system graph is too complex, the overall time required for the schedulability check can be exponential with respect to the size of services and service implementations; this may lead to an unbounded reconfiguration time. In this paper, we present an approach to reduce the complexity of the system graphs so that a summarizing one that contains valid solutions is analyzed and not the complete system graph. We have implemented this mechanism inside the iLAND service reconfiguration and composition components to validate the proposed concepts and ideas; the reduction of the space of solutions with the presented approach is very high, which dramatically decreases the computation time of the reconfiguration process.     

路面施工机械机群智能控制系统

针对国内路面施工的现状和存在的问题，结合施工机械本身的特点，对施工机械智能机群系统的控制结构及通信方式进行了研究，给出了基于无线局域网的施工机械智能机群系统的整体结构框架，对单个机械重点介绍了如何使用CAN总线实现一个分布式实时控制系统，并对单机控制的软件结构及嵌入式实现方法进行了探讨。     

混合现场总线控制系统的实时性分析

根据当前混合现场总线控制系统的系统构架,对FF H1现场总线系统、Profibus-DP现场总线系统以及由它们构成的混合现场总线系统进行了实时性分析.给出了混合现场总线系统控制周期、总线宏周期和报文循环时间的设置和计算方法,为工程设计人员设计混合现场总线系统提供了重要参考依据.最后,说明了对混合现场总线进行实时性分析具有重要的理论价值和实用价值.     

Pre-run-time scheduling in real-time systems: Current researches and Artificial Intelligence perspectives

This paper presents the taxonomy of real-time systems with special emphasize on pre-run-time scheduling problem. Firstly, we present real-time systems, real-time tasks, timing, precedence and exclusion constraints. Then, we describe the problem of pre-run-time scheduling of tasks under constraints. After that, we present the most existing efficient techniques to deal with the latter problem. We summarize the discussion of existing techniques and possible research perspectives after surveying the Artificial Intelligence’s point of view about the problem of pre-run-time scheduling of real-time tasks. The Artificial Intelligence survey includes Constraint Satisfaction Problems class since pre-run-time scheduling belongs to the latter class. The Artificial Intelligence survey includes also Path-finding Problems from which intelligent algorithms could be observed such as Learning-Real-Time-A1(LRTA1) thanks to its important properties (optimality, linear space complexity and determinism). The development of an algorithm like LRTA1 to solve Constraints Satisfaction Problems and particularly the pre-run-time scheduling of real-time tasks problem is one clear research direction to deal with large-scale real-time systems. The overall objective of this paper is to show what are the perspectives to Artificial Intelligence literature that could be beneficial firstly to Artificial Intelligence community itself and secondly to real-time systems community.     

多水下机器人视景仿真系统技术研究

该文介绍了多水下机器人群体分佰式智能控制软件的视景仿真系统。以MultiGen Creator建模,利用实时视景开发软件包OpenGL Performer,采用POSIX Thread多线程技术,在Linux环境下开发了分布式多水下机器人三维视景仿真平台。实现了多水下机器人分布式智能控制软件系统的实时视景仿真,保证了整个系统的信息共享与时间同步。同时该文讨论了该视景仿真软件的开发过程以及整个系统的体系结构和信息流程。试验结果表明,该视景系统可逼真演示多水下机器人编队水下航行、作业等过程,并满足系统仿真的实时性要求。     

Distributed measurement and control system based on microcontrollers with automatic program generation

The paper describes an open architecture microcontroller based distributed measurement and control system with automatic generation of application program. Interpretation of functions and generation of program for control of the newly added distributed unit or distributed unit of a new type connected to the system performs automatically, without user assistance. The elements of the system are interconnected by means of a serial common bus according to the reduced OSI protocol. The proposed concept was tested in a system developed by using 8-bit Atmel microcontrollers of 89S and 89C series. Apart from the central unit, intelligent distributed units were developed for the control of a stepper motor, programmable linear movement, control of halogen lamps, acquisition and generation of analogue, digital and timing pulses and a real time clock (RTC).     

Reflective knowledge models to support an advanced HCI for decision management

In the previous years, the evolution of the telematics technology has introduced a new scenario of human–computer operation where the achievement of an adequate level of user–system interaction has become a key aspect. This issue is specially relevant in real-time management scenarios where the system is intended to provide an intelligent support to human operators in the decision-making task. This paper proposes the use of advanced knowledge-based models to support human–computer interaction in the context of real-time decision for management problems. The approach is mainly based on endowing intelligent systems with an introspection capability that makes possible an adaptive performance to the characteristics of the interaction. This capability is supported by a reflective architecture where a metalevel layer dynamically configures reasoning strategies to generate the required answers by looking into a structured collection of problem-solving components. The approach was developed and applied within the FLUIDS project, an European Commission Telematics Applications research project. The proposal is illustrated with an example in the domain of real-time private traffic management in the city of Turin.     

基于Multi-Agent的分布式智能视觉监控系统研究

90年代以来,随着计算机技术的发展,对于Agent的研究已经成为分布式人工智能领域的一个热点,基于Multi-Agent的分布式智能系统已成功地应用于众多领域。该文将Multi-Agent技术应用于智能视觉监控领域,以开发智能视觉监控的分布式Multi-Agent系统,提出了系统的基本框架和系统实现途径及方法,其中着重研究了基于Multi-Agent理论的视觉监控系统模型、组织活动,以及多Agent之间的协调合作问题。该分布式系统的研究,为实际应用系统的研制开发提供了理论指导和方法依据。     

基于协进化机制的Multi-agent分布式智能控制体系

提出了一种基于协进化机制的多Agent分布式智能控制体系结构，采用划分基本行为模块的方法，将复杂、分布的控制系统构造成基于行为的、行为活性状态可调控的多Agent系统，并设计了基于协进化机制的分布式并行协进化学习机构及其协进化算法，使系统能分布并行地协进化各基本行为规则库和全局行为协调规则库。该体系结构能简单而有效地使系统的局部控制及全局行为协调协作具有较好的在线学习、自适应特性，系统可扩展性强，有较好的实用性，能应用于资源受限的嵌入式控制系统。     

基于中间件技术的远程实时监测系统

重点介绍了一种新型的基于中间件技术的分布式远程实时监测与诊断系统,提出了由数据采集层、中间件应用服务器层、数据发布层组成的多层分布式实时监测系统模型;并针对中间件服务器层所涉及的一些关键技术进行了论述。设计了能够可靠传输实时监测数据的应用层协议,应用该模型和方法开发的远程实时监测与诊断系统在石化企业得到实现与验证。     

Improving the predictability of distributed stream processors

Next generation real-time applications demand big-data infrastructures to process huge and continuous data volumes under complex computational constraints. This type of application raises new issues on current big-data processing infrastructures. The first issue to be considered is that most of current infrastructures for big-data processing were defined for general purpose applications. Thus, they set aside real-time performance, which is in some cases an implicit requirement. A second important limitation is the lack of clear computational models that could be supported by current big-data frameworks. In an effort to reduce this gap, this article contributes along several lines. First, it provides a set of improvements to a computational model called distributed stream processing in order to formalize it as a real-time infrastructure. Second, it proposes some extensions to Storm, one of the most popular stream processors. These extensions are designed to gain an extra control over the resources used by the application in order to improve its predictability. Lastly, the article presents some empirical evidences on the performance that can be expected from this type of infrastructure.