相关任务图的一种有效并行调度算法

对3个典型的表调度算法：MCP算法，ETF算法和BDCP算法进行了分析，发现它们均不能确保任务最早调度。通过综合考虑IBN、CBN和OBN3类结点对调度结果的影响，提出了一个更加有效的基于关键路径的表调度算法，该算法能够确保关键路径结点具有最早启动时间，从而能有效缩短任务图的调度长度。分析和仿真结果表明，该调度算法不仪具有合理的算法复杂性，而且能有效地缩短相关任务图的调度长度，优于MCP、ETF、BDCP算法。     

一类SISO系统的结构奇异值u综合

具有两个标量不确定性的结构化不确定性ＳＩＳＯ系统μ综合一般是通过闭环系统μ值的上界函数ｉｎｆσ来完成的。本文给出了这种情况下μ值及其上界函数中的Ｄ阵元素的显式表达式，从而使μ分析尤其是μ综合的计算最减少很多，并给出了应用Ｄ阵元素的显式表达式的μ综合算法和一个算例。     

基于邻结点表的MANET网络路由协议

本文先分析了当前MANET系统中的路由协议，提出了一种基于邻结点表的路由协议算法，利用邻结点信息，提高了路由的自我维护能力。最后通过仿真实验，验证了该算法的有效性。     

智能表广播模型

紧密耦合系统中的广播模型仍是现代网络系统中讨论的重点之一,现今经常使用的广播模型的如传统广播模型及全局表模型都由于没有充分发挥软件的功能而具有较大的局限性。对此,作者提出了一种新的智能表广播模型ＩＬＢＭ。在该模型中每一结点都被赋予一个邻结点表与一个结点算法,由结点算法来灵活决定结点在广播过程中对各连接的转发顺序,从而以软件表态形式上的一致实现运行效果的不一致,进而统一表;     

决策树的优化算法

决策树的优化是决策树学习算法中十分重要的分支.以ID3为基础,提出了改进的优化算法.每当选择一个新的属性时,算法不是仅仅考虑该属性带来的信息增益,而是考虑到选择该属性后继续选择的属性带来的信息增益,即同时考虑树的两层结点.提出的改进算法的时间复杂性与ID3相同,对于逻辑表达式的归纳,改进算法明显优于ID3.     

Mesh网络路由算法容错性的概率分析

该文基于k-Mesh子网的概念提出了两个简单的基于局部信息和分布式的Mesh网络容错路由算法，并对其容错性进行概率分析；在每个结点具有独立的出错概率的假设条件下，推导出路由算法成功返回由正确结点组成的路径的概率．该文运用严格的数学推理，证明了Mesh网络结点出错概率只要控制在1．87％以内，则对于多达几十万个结点的Mesh网络，提出的路由算法具有99％的概率确保找到正确结点组成的路径．路由算法的时间复杂性是线性的．模拟结果表明路由算法所构造的路由路径长度非常接近于两结点之间的最优路径长度．     

基于基因表达式的克隆选择算法求解JSP问题

针对作业车间调度问题的特征,提出一种基于基因表达式的克隆选择算法。在这个方法中,采用基因表达式编程算法中的编码方式来表示调度方案,同时为了提出的方法具有更强的全局搜索能力,运用克隆选择算法作为搜索引擎。最后,验证提出的方法的有效性,对7组Benchmark实例进行测试。实验结果表明,基于基因表达式的克隆选择算法在求解作业车间调度问题中是非常有效的。     

基于XML的数据查询效率优化方法的研究

为了提高XML数据查询处理效率,提出时XML数据结点采用标签聚类存储,同时结点路径信息存储在位向量中.通过XML Schema和查询信息计算出结点过滤表达式,由位向量间的高效运算剔除不满足过滤表达式的结点.另外给出压缩位向量后对压缩数据直接进行过滤操作的方法.实验结果表明该优化方法对XML的数据查询具有较高效率.     

基于多值方法的模糊逻辑函数最小化

首先提出了模糊逻辑和多值逻辑的相似性，并从开关信号理论出发建立了三值逻辑函数阈运算和模糊逻辑函数文字运算的对应关系，进而提出了基于差动电流开关理论的三值逻辑函数化简法求模糊逻辑函数最小化表达式的算法，并用该算法对几个模糊逻辑函数实例进行了化简，实例操作表明，该算法具有操作简单快捷的特点，是获得模糊逻辑函数最小化表达式的一种有效的方法。     

基于对等结点指针表优化的 Chord 算法改进

对等网络需要解决的一个关键性问题是如何有效地查找存储所需资源的结点.文中在研究分布式查找算法Chord 的基础上,介绍了分布式哈希表(DHT)的主要思想,阐述了资源关键字查找方式,重点分析结点指针表的特性及其表中冗余信息对查找资源的影响,进而提出了覆盖冗余信息的方法(URFChord)改进结点指针表. URFChord 方法首先要计算指针表的冗余量 R(N),然后在不增大指针表存储空间的情况下,删除指针表冗余信息再添加 R(N)个新的路由信息.通过性能分析及仿真实验,证实了这种改进方法的可行性和有效性,减少了平均查找路径长度,提高了查询效率     

An assignment method for IPUs in distributed systems

In a distributed system,one of the most important thing is to establish an assignment method for distributing tasks.It is assumed that a distributed system does not have a central administrator,all independent processing units in this system want to cooperate for the best results,but they cannot know the conditions of one another,So in order to undertake the tasks in admirable proportions,they have to adjust their undertaking tasks only by selt-learning.In this paper,the performance of this system is analyzed by Markov chains,and a robust method of self-learning for independent processing units in this kind of systems is presented.This method can lead the tasks of the system to be distributed very well among all the independent processing units,and can also be used to solve the general assignment problem.     

基于马尔科夫链自适应能力任务分派系统设计

当分布式系统中各处理结点相互完全独立,并且在对其他结点的状态不是很了解情况下,利用组合数学和随机过程的方法提出一种机制,该机制能使各结点在没有全局管理者的参与下,仅根据系统运行的反馈决定下一步的任务,从而使整个系统的任务分配达到最优。该方法能很好地处理最普遍的任务分派问题。     

利用位置和加速度反馈的矩阵二阶系统特征结构配置

考虑一类利用位置和加速度反馈二阶线性系统的特征结构配置问题．在允许闭环系统的特征值是未知的前提下,结合矩阵多项式的右互质分解提出二阶线性系统特征结构配置的参数化方法,建立反馈增益阵和特征向量矩阵的显示参数化表达式．本文涉及的参数化方法直接将二阶系统模型转化为一阶状态空间形式,从而降低了系统设计中的计算工作量,并且提出的算法简单,无“返回”步骤．最后,数值算例表明了该算法的有效性．     

面向抖动优化的任务静态优先级指派算法

对任务相对截止时限进行优化设置是一种减少输出抖动的有效方法,但现有方法均是针对最早时限优先调度算法,不能适用于任务集采用静态优先级调度算法的场合.为此,提出通过优化优先级指派实现任务集的整体抖动最小化,并给出一种启发式的优先级指派算法.根据单调速率调度算法确定任务的初始优先级,以最小化局部抖动方式依次对任务的优先级进行再调整,从而得到近似最优的优先级指派.仿真实验结果表明,该算法能有效减少任务集的整体输出抖动.     

Two parametric approaches for eigenstructure assignment in second-order linear systems

This paper considers eigenstructure assignment in second-order linear systems via proportional plus derivative feedback . It is shown that the problem is closely related to a type of so-called second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two complete parametric methods for the proposed eigenstructure assignment problem are presented. Both methods give simple complete parametric expressions for the feedback gains and the closed-loop eigenvector matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows the closed-loop eigenvalues to be set undetermined and sought via certain optimization procedures. An example shows the effectiveness of the proposed approaches.     

Characteristic multiplier assignment in continuous-time linear periodic systems

A characteristic multiplier assignment problem for continuous-time periodic systems with analytic coefficients is considered. First, the necessary and sufficient condition for controllability is shown. Under this condition, an algorithm for assigning a set of characteristic multipliers is proposed. The algorithm is constructed by a simple repetitive procedure, and is suited to computer programming. The given feedback gain matrix is composed of a sequence of Dirac delta functions; such a feedback system can easily be implemented using proper approximation to the delta function. Lastly, the design method is applied to the attitude control problem of a spin-stabilized satellite, and some simulation results are given.     

An efficient approach for the multiprocessor non-preemptive strictly periodic task scheduling problem

Strict periodicity constraint is of great importance since it concerns some hard real-time systems where missing deadlines leads to catastrophic situations. However, the problem of schedulability analysis for non-preemptive strictly periodic tasks on a multiprocessor platform is even more intractable than the one with the common periodicity. In order to implement such systems, designers need effective tools based on fast and near-optimal solutions.This paper presents a schedulability analysis which results mainly in a, two versions, task assignment and start-time calculation algorithm. The first one targets the harmonic task periods case while the second one targets the non-harmonic task periods case. Each version is based on a sufficient uniprocessor schedulability test. In addition, for the non-harmonic case which is the most intractable, the uniprocessor sufficient schedulability test uses the strictly periodic task utilization factor. This factor stands for the fraction of time spent to execute a task while its strict periodicity and the ones of the already scheduled tasks are met. As a result, an efficient and easily implementable scheduling algorithm is proposed which begins by assigning tasks to processors then attributes a start-time to every task in such a way that strict periodicity and deadline constraints are met. The effectiveness of the proposed scheduling algorithm, in both versions, has been shown by a performance evaluation and comparisons with an optimal and a similar suboptimal solution.     

ESOM: An expert system for multicriteria scheduling

There exist situations in operations scheduling where the parameters of the scheduling decision are nonquantifiable, or appear as nonnumerical entries in a database. Scheduling techniques based on numerical algorithms may be difficult to use in such situations. In many service industries, the nonnumerical character arises from constraints or preference parameters associated with service tasks, service agents, and the business operation itself. The agent to task assignment problem is one of satisfying multiple objectives, by taking into account the various constraints and preferences inherent in such problems. In this paper, we describe the development of an expert system prototype called ESOM, that aims to automate the assignment decision process of a childcare referral agency. We discuss some key research issues pertaining to service scheduling in general, and to the childcare assignment problem in particular. ESOM provides useful guidelines to future researchers and practitioners interested in building expert systems for service scheduling. We demonstrate assignments made by our prototype through an application scenario.     

Eigenstructure assignment in a class of second-order dynamic systems

Eigenstructure assignment using the proportional-plus-derivative feedback controller in a class of secondorder dynamic system is investigated. Simple, general, complete parametric expressions for both the closed-loop eigenvector matrix and the feedback gains are established based on two simple Smith form reductions. The approach utilizes directly the original system data and involves manipulations only on n?dimensional matrices. Furthermore, it reveals all the degrees of freedom which can be further utilized to achieve additional system specifications. An example shows the effect of the proposed approach.