A Constraint-Based Approach to Assigning System Components to Tasks

In multi-component systems, individual components must be assigned to the tasks that they are to perform. In many applications, there are several possible task decompositions that could be used to achieve the task, and there are limited resources available throughout the system. We present a technique for making task assignments under these conditions. Constraint satisfaction is used to assign components to particular tasks. Heuristics suggest a task decomposition for which an assignment can be found efficiently. We have applied our technique to the problem of task assignment in systems of underwater robots and instrument platforms working together to collect data in the ocean.     

Constraint-Based Facial Animation

Constraints have been traditionally used for computer animation applications to define side conditions for generating synthesized motion according to a standard, usually physically realistic, set of motion equations. The case of facial animation is very different, as no set of motion equations for facial expressions is available. In this paper we discuss a facial animation editor, which uses numerical constraints for two roles: to declare the mimic repertoire of synthetic faces and other requirements a facial animation has to meet, and to aid the animator in the process of composing a specific animation fulfilling the requirements. The editor is thus also a ``motion sculpturing' tool, which lifts the task of creating facial animation from the control data manipulation level to the conceptual design level. The major aid of the editor is to repair inconsistencies due to changes made by the user, and revise changes for which no good repair is possible. Also, reuse of constrained animations, especially expressions, is supported. The main machinery behind these services is interval propagation, which, if using certain type of linear inequalities to express the character- as well as the animation-specific requirements, can produce quickly the interval of feasible values for each control variable. If a solution (usually, repair) has to be produced, it is generated by selecting the best one from a restricted set of acceptable solutions, based on user-defined or automatically generated criteria for the choices.     

光突发交换网络中的重调度算法

介绍了光突发交换（OBS）网络,在现有算法LAUC_VF的基础上提出了一种重调度算法,即LAUC_VF_RESCHEDULE算法,它的主要思想是：对新到达的突发运用LAUC_VF算法调度不成功时,将已经调度成功的突发从原有信道Ⅰ重新调度到另一数据信道J上,并保持该突发的到达时刻和结束时刻不变,从而将新到达的突发调度到数据信道Ⅰ上。仿真结果表明在大多数情况下该重调度算法相对于LAUC_VF算法对网络性能的改善是比较大的。     

Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods

Many manufacturing facilities generate and update production schedules, which are plans that state when certain controllable activities (e.g., processing of jobs by resources) should take place. Production schedules help managers and supervisors coordinate activities to increase productivity and reduce operating costs. Because a manufacturing system is dynamic and unexpected events occur, rescheduling is necessary to update a production schedule when the state of the manufacturing system makes it infeasible. Rescheduling updates an existing production schedule in response to disruptions or other changes. Though many studies discuss rescheduling, there are no standard definitions or classification of the strategies, policies, and methods presented in the rescheduling literature. This paper presents definitions appropriate for most applications of rescheduling manufacturing systems and describes a framework for understanding rescheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches that have been described in the rescheduling literature. The paper also discusses studies that show how rescheduling affects the performance of a manufacturing system, and it concludes with a discussion of how understanding rescheduling can bring closer some aspects of scheduling theory and practice.     

New Grid Scheduling and Rescheduling Methods in the GrADS Project

The goal of the Grid Application Development Software (GrADS) Project is to provide programming tools and an execution environment to ease program development for the Grid. This paper presents recent extensions to the GrADS software framework: a new approach to scheduling workflow computations, applied to a 3-D image reconstruction application; a simple stop/migrate/restart approach to rescheduling Grid applications, applied to a QR factorization benchmark; and a process-swapping approach to rescheduling, applied to an N-body simulation. Experiments validating these methods were carried out on both the GrADS MacroGrid (a small but functional Grid) and the MicroGrid (a controlled emulation of the Grid).     

A Constraint-Based Robotic Soccer Team

It is a challenging task for a team of multiple fast-moving robots to cooperate with each other and to compete with another team in a dynamic, real-time environment. For a robot team to play soccer successfully, various technologies have to be incorporated including robotic architecture, multi-agent collaboration and real-time reasoning. A robot is an integrated system, with a controller embedded in its plant. A robotic system is the coupling of a robot to its environment. Robotic systems are, in general, hybrid dynamic systems, consisting of continuous, discrete and event-driven components. Constraint Nets (CN) provide a semantic model for modeling hybrid dynamic systems. Controllers are embedded constraint solvers that solve constraints in real-time. A controller for our robot soccer team, UBC Dynamo98, has been modeled in CN, and implemented in Java, using the Java Beans architecture. A coach program using an evolutionary algorithm has also been designed and implemented to adjust the weights of the constraints and other parameters in the controller. The results demonstrate that the formal CN approach is a practical tool for designing and implementing controllers for robots in multi-agent real-time environments. They also demonstrate the effectiveness of applying the evolutionary algorithm to the CN-modeled controllers.     

The Localization and Correction of Errors in Models: A Constraint-Based Approach

Model-based diagnosis, and constraint-based reasoning are well known generic paradigms for which the most difficult task lies in the construction of the models used. We consider the problem of localizing and correcting the errors in a model. We present a method to debug a model. To help the debugging task, we propose to use the model-base diagnosis solver. This method has been used in a real application of the development a model of a railway signalling system.     

资源动态组织支持的网格依赖任务重调度机制

针对网格依赖任务重调度所面临的效率低与触发频繁的问题,提出资源动态组织支持的网格依赖任务调度机制.该机制以资源的动态组织为核心,基于资源动态性度量结果对资源进行性能聚类分析,并过滤性能相似资源中的强动态性资源,以在减少资源数量的同时提高重调度备选资源的稳定性.实验表明基于该机制的重调度算法保持了静态调度策略在动态网格环境下相对于动态调度策略的性能优势,从而验证了该机制解决网格依赖任务重调度所面临问题的有效性.     

基于约束的可定制产品配置模型

在分析可定制产品概念及其结构特点的基础上，通过采用可定制产品的形式化建模方法，实现了对可定制产品配置模型与可定制产品数据BOM的构建．利用可定制产品配置模型中的约束条件及相应的产品数据BOM的分解算法，并配合工程数据库技术，降低了企业产品数据管理的冗余和低效，实现了可定制产品数据在企业各部门间的集成、共享及一致性控制．     

Constraint-Based Design of Embedded Intelligent Systems

Substantial progress has been achieved using the standard Constraint Satisfaction Problem framework. However, there is a major unsolved challenge confronting the constraint research community: the constraint-based design of embedded intelligent systems. This requires a new online model of constraint satisfaction and new computational tools for specifying, modeling, verifying and implementing constraint-based, hybrid, intelligent systems, such as robots. The Constraint Net model of Zhang and Mackworth allows the design of hybrid intelligent systems as situated robots: modeling the robot and the environment symmetrically as dynamic systems. If the robot's perceptual and control systems are designed as constraint-satisfying devices then the total robotic system, consisting of the robot symmetrically coupled to the environment, can be proven correct. Some theoretical and practical advances based on this model are described, including experiments with the constraint-based design of robot soccer players.     

Rolling Partial Rescheduling with Dual Objectives for Single Machine Subject to Disruptions

This paper discusses the single-machine rescheduling problem with efficiency and stability as criteria, where more than one disruption arises in large-scale dynamic circumstances. Partial rescheduling (PR) strategy is adopted after each disruption and a rolling mechanism is driven by events in response to disruptions. Two kinds of objective functions are designed respectively for PR sub-problem involving in the interim and the terminal of unfinished jobs. The analytical result demonstrates that each local objective is consistent with the global one. Extensive computational experiment was performed and the computational results show that the rolling PR strategy with dual objectives can greatly improve schedule stability with little sacrifice in efficiency and provide a reasonable trade-off between solution quality and computational efforts.     

多次扰动下单机双目标的滚动部分重调度

This paper discusses the single-machine rescheduling problem with efficiency and stability as criteria, where more than one disruption arises in large-scale dynamic circumstances. Partial rescheduling (PR) strategy is adopted after each disruption and a rolling mechanism is driven by events in response to disruptions. Two kinds of objective functions are designed respectively for PR sub-problem involving in the interim and the terminal of unfinished jobs. The analytical result demonstrates that each local objective is consistent with the global one. Extensive computational experiment was performed and the computational results show that the rolling PR strategy with dual objectives can greatly improve schedule stability with little sacrifice in efficiency and provide a reasonable trade-off between solution quality and computational efforts.     

Structure and Simulation Evaluation of an Integrated Real-Time Rescheduling System for Railway Networks

A critical problem faced by railways is how to increase capacity without investing heavily in infrastructure and impacting on schedule reliability. One way of increasing capacity is to reduce the buffer time added to timetables. Buffer time is used to reduce the impact of train delays on overall network reliability. While reducing buffer times can increase capacity, it also means that small delays to a single train can propagate quickly through the system causing knock-on delays to trains impacted by the delayed train. The Swiss Federal Railways (SBB) and Swiss Federal Institute of Technology (ETH) are researching a new approach for real-time train rescheduling that could enable buffer times to be reduced without impacting schedule reliability. This approach is based on the idea that if trains can be efficiently rescheduled to address delays, then less buffer time is needed to maintain the same level of system schedule reliability. The proposed approach combines a rescheduling algorithm with very accurate train operations (using a driver-machine interface). This paper describes the proposed approach, some system characteristics that improve its efficiency, and results of a microscopic simulation completed to help show the effectiveness of this new approach. The results demonstrate that the proposed integrated real-time rescheduling system enables capacity to be increased and may reduce knock-on delays. The results also clearly showed the importance of accurate train operations on the rescheduling system’s effectiveness.     

基于指令聚类与指令调度的嵌入式软件功耗优化研究

选用指令级能耗评估模型，提出和验证了一种基于指令聚类与指令调度的功耗优化方案．该方案采用深度优先算法搜索局部最优解，挑选出能耗较小的一种指令序列．又兼顾测试工作量与精确度，将能耗相似的指令归入同类，有效降低了获取相邻指令切换能耗参数的工作量过大这一问题．通过分析基于SimpleSealar／Wattch模拟器的实验结果，指出仅用指令调度技术进行指令级功耗优化，其效果有限，为了提高优化效率，必须进行更高级别的功耗评估与优化．     

A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.     

Icola — Incremental Constraint-Based Graphics for Visualization

Visualization is valuable in monitoring and debugging programs. The goal of the Wand research project at the University of Saskatchewan is to provide both a framework and tools for rapid development of visualization aids for logic programming languages. The ICOLA (Incremental Constraint-based Object Layout Algorithm) system is the newest graphics facility within Wand. ICOLA positions graphical objects according to object declarations and constraints specifying relative positional relationships among the objects. Three important features of ICOLA are that it is capable of creating reasonable pictures from highly under-constrained specifications, it uses an incremental constraint solution algorithm and hence generates those pictures efficiently, and it supports incremental (i.e. progressive) insertions and deletions of objects and constraints. The ability of the incremental algorithm to support such deletions is particularly noteworthy. This paper describes: PDI, the language supported by ICOLA; the incremental constraint solution algorithm itself; a successful implementation in Prolog and C; and results of a performance evaluation of the implementation.     

Predictive, Stochastic and Dynamic Extensions to Aversion Dynamics Scheduling

Schedulers' decisions in real factories deal with perceived risks and impacts. They proactively anticipate and reactively mitigate risky events by altering what would be considered a normal schedule to minimize associated impacts. These risk mitigation concepts are called aversion dynamics (AD). Aversion dynamics describes the aversion that jobs exhibit to impacts resulting from risky events in dynamic and unstable production environments. The aversion manifests itself in either advancing or delaying the work to avoid the risky period. This paper extends the first AD heuristic, Averse-1, to capture additional real-world dynamics and to make the heuristic predictive (proactive) as to when the perceived risky event may happen. In particular, predictive and stochastic elements are incorporated within a dynamic job arrival framework to create an extended heuristic called Averse-2.     

一种改进的基于约束关系的XML查询重写算法研究

查询重写是解决数据集成、查询优化和物理层数据独立性等问题的关键技术.以往工作主要集中在关系数据模型方面.最近Michigan大学Timber研究小组提出一种全新的基于约束的XML查询重写算法.然而,该算法未考虑存在内定谓词情况下的重写问题,应用范围受到一定限制.在原算法的重写思想基础上,提出了一种基于约束的XML查询重写的改进算法.通过引入映射规则中的约束条件,消除阻碍重写的Skolem函数,从而解决内定谓词问题,增大原算法的应用范围.证明了改进算法的正确性.性能分析和测试结果表明,改进算法并不增加实质性的性能代价.