基于分布对象的高性能异步回调模型

分布对象技术是分布异构环境下软件开发和系统集成的良好解决方案 ,然而在高性能分布计算领域 (如分布事务处理、分布交互仿真和分布并行计算 ) ,传统调用模型在异步特性方面的不足限制了分布对象技术在该领域的应用。因此 ,文章介绍一个新的基于分布对象的异步回调模型 ,着重探讨了该模型的定义、关键实现技术、优化策略和性能测试。     

支持多媒体应用的CPU调度模型

多媒体应用的出现对操作系统调度模型提出了新的要求，许多多媒体系统中既有硬、软实时应用程序，又有传统的分时应用程序，希望在同一操作系统框架内得到支持。本文提出了支持上述功能的ＣＰＵ调度模型，并设计了两种算法来实现该模型：基于ＱｏＳ的ＣＰＵ带宽划分算法和双优先级调度算法。     

大规模串行分布式检测的性能

串行分布式（Ｎ＝２,３,４）检测的最优协调门限组难以求取,因而只能就由少量传感器组成的小规模串行网,通过数值计算来考察检测性能。本文在一定条件下,给出了求取串行分布式检测性能的解析方法,进而可得到大规模串行分布式检测的性能,使我们能考察和了解检测性能在积累数增加时的变化趋势。     

舰载分布式火控系统功能备份、重组和恢复的一种设计与实现方法

以一个舰载分布式火控模拟系统为背景,给出一种系统功能备份、重组和恢复的设计与实现方法。主要介绍设计要求、备份策略、检测机制和分级实现。实验表明,系统在损失近５０％设备时仍能维持原功能工作,在损失７０％以上时尚能继续运行,从而证明了该方法的正确、可行和有效     

两人分布动态决策系统建模研究

本文提出的建模方法之原理为：两人决策时每人的内部功能是主体基础,人员队中协作为外表行为,人对目标（任务）的比较选择过程为直观的快速估算（简称：内主、外协、快速估算）。这是两人队决策建模方法的新创造。新建成数学模型的有效性与水平都作了检验与评价,结果令人满意     

用于军事态势估计的协作知识模型

分布式人工智能（ＤＡＩ）是ＡＩ领域的一个新分支。ＤＡＩ研究的主要目的在于分析和设计大型复杂的协作智能系统。本文以军事智能决策过程中的重要环节──态势估计任务为背景,提出了用于实现分布式协作求解的知识表示框架ＤＥＳＷ系统。文章简要分析了军事态势估计领域背景,然后从系统设计的三个方面依次介绍了ＤＥＳＷ的系统组织模型、主体概念模型和分布式协作推理模型。     

基于任务和角色的分布式工作流安全模型

针对现有基于角色访问控制的缺陷和分布式工作流管理系统的特性,在传统的基于角色的访问控制模型中引入任务集(Tasks)、任务实例集(TaskInstances)和任务上下文(TaskContext)的概念,将传统的user role permission权限赋予结构修改为user role task permission权限赋予结构,建立了基于任务和角色的访问控制模型,给出了其形式化定义。该模型解决了传统的基于角色访问控制中的动态适应性差和最小权限约束假象的问题,用于分布式工作流管理系统,提高了安全性、实用性。     

Due‐window assignment with unit processing‐time jobs

In due‐window assignment problems, jobs completed within a designated time interval are regarded as being on time, whereas early and tardy jobs are penalized. The objective is to determine the location and size of the due‐window, as well as the job schedule. We address a common due‐window assignment problem on parallel identical machines with unit processing time jobs. We show that the number of candidate values for the optimal due‐window starting time and for the optimal due‐window completion time are bounded by 2. We also prove that the starting time of the first job on each of the machines is either 0 or 1, thus introducing a fairly simple, constant‐time solution for the problem. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

模糊合成算子在作战方案综合评估的应用研究

在分布式交互仿真中,根据仿真结果对作战方案进行综合评估,运用模糊综合评判的方法进行评判,并着重对合成算子的选择进行分析,确定乘与有界算子M(·, )为比较适合对作战方案评估的算子.     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.