Performance analysis of an adaptive dynamic grid-based approach to data distribution management

Data distribution management (DDM) plays a key role in traffic control for large-scale distributed simulations. In recent years, several solutions have been devised to make DDM more efficient and adaptive to different traffic conditions. Examples of such systems include the region-based, fixed grid-based, and dynamic grid-based (DGB) schemes, as well as grid-filtered region-based and agent-based DDM schemes. However, less effort has been directed toward improving the processing performance of DDM techniques. This paper presents a novel DDM scheme called the adaptive dynamic grid-based (ADGB) scheme that optimizes DDM time through the analysis of matching performance. ADGB uses an advertising scheme in which information about the target cell involved in the process of matching subscribers to publishers is known in advance. An important concept known as the distribution rate (DR) is devised. The DR represents the relative processing load and communication load generated at each federate. The DR and the matching performance are used as part of the ADGB method to select, throughout the simulation, the devised advertisement scheme that achieves the maximum gain with acceptable network traffic overhead. If we assume the same worst case propagation delays, when the matching probability is high, the performance estimation of ADGB has shown that a maximum efficiency gain of 66% can be achieved over the DGB scheme. The novelty of the ADGB scheme is its focus on improving performance, an important (and often forgotten) goal of DDM strategies.     

基于权重函数的混合DDM算法

高层体系结构已成为分布式仿真通用技术框架的核心,其中数据分发管理服务则为其提供了有效的数据过滤机制.目前常用的几种DDM算法,如基于区域的算法、基于网格的算法和简单混合的算法(基于网格的DDM和基于区域的DDM混合使用)等都存在着一些不足.基于权重函数的混合DDM算法是在简单混合的DDM算法基础上加入了对路经空间中所划分网格的权重函数设立机制和对冗余信息、虚假信息的控制机制.实验结果表明,该算法在减少算法执行时间,尤其是降低网络中的数据传输量和减少组播地址消耗方面,体现出良好的性能,进一步满足了系统的可扩缩性要求.     

集中式MIMO雷达研究进展：正交波形设计与信号处理

集中式多输入多输出（Multiple Input Multiple Output,MIMO）雷达通常利用正交波形增加发射波形自由度,采用数字阵列拓展空间收发自由度,使得雷达接收机的天线孔径获得明显扩展,最终带来空间分辨率、测角精确度、杂波抑制能力等大幅度提升。但是,这些性能提升的前提是发射波形具有正交特性。事实上,在实际应用中,在不牺牲时域/频域资源情况下,受限于时宽带宽积,无法获得完全正交的波形集合,从而限制了MIMO雷达系统性能。本文对集中式MIMO雷达正交波形复用的技术原理进行了系统回顾,分别归纳了三种快时间发射波形设计方法：时分复用（Time Division Multiplexing, TDM）、码分复用（Code Division Multiplexing,CDM）和频分复用 （Frequency Division Multiplexing, FDM）,以及两种慢时间发射波形设计方法：多普勒分复用（Doppler Division Multiplexing,DDM）和随机相位编码波形,并对其优缺点进行对比。同时,对快时间MIMO和慢时间MIMO的信号处理流程进行归纳综合,给出基于匹配滤波的集中式MIMO雷达统一信号处理框架。为了展示不同波形对成像性能的影响,本文给出了基于三维匹配滤波的MIMO雷达成像结果。最后,结合实际应用问题,指出当前MIMO雷达面临的技术难点和发展趋势。     

基于元胞自动机的分布式数据挖掘分类器

针对常用分类方法分类精度较低和内存消耗较高的问题,设计一种基于多吸引子元胞自动机（MACA）的模式分类器tsPCM,把它应用于分布式数据挖掘。通过改变MACA的描述方法,用依赖串和依赖向量将分类过程设计成两阶段,用遗传算法优化设计。实验结果表明tsPCM具有较高的分类精度和较低的内存消耗,分类复杂度由O（n^3）降低到线性级O（n）,具有较好的应用价值。     

二维Helmholtz方程外问题基于自然边界归化的重叠型区域分解算法

１．引 言 设是平面光滑闭曲线,是以为边界的外部区域,考虑二维Ｈｅｌｍｈｏｌｔｚ方程外Ｎｅｕｍａｎｎ问题并在无穷远处满足Ｓｏｍｍｅｒｆｅｌｄ辐射条件其中是区域的边界的外法线方向,即指向由包围的内部区域．κ在许多情况下（例如约化波动方程）是实数,在另一些情况下则是纯虚数．本文仅讨论κ为纯虚数的情况,且不失一般性,可设Ｉｍ（ｋ）＞０． 用某些数值方法求解线性抛物型方程或线性双曲型方程的初边值问题时,可能导致求解Ｈｅｌｍｈｏｌｔｚ方程的外问题．例如,用自然边界元法求解线性抛物型方程的初边值问题时就导致求…     

聚类的组播组分配策略在DDM中的实现

DDM(DataDistributionManagement)服务是高层体系结构HLA(HighLevelArchitecture)中定义的六大服务之一,它主要目的是通过减少网络间不相关数据的分发,提高网络的利用效率。一种常用的DDM优化方法是使用组播,组播是一种非常适合一对多的通信方式,它能够将更新数据发送到一个指定的定购者子集里。传统的DDM组播使用固定网格分配算法,在资源使用和数据发送方面存在一定的问题,不适合超大规模的仿真。本文在固定网格算法基础上提出了一种基于聚类的组播组分配算法,通过聚类,将固定网格的组播组进行合并,减少组播组的使用数量,提高网络资源的利用率,最后从实验结果上分析了聚类组播算法的优缺点。     

一种用于数据分布管理的模糊DR算法

为了满足分布式交互仿真（DIS）中数据分布管理（DDM）对可扩展性和信息过滤的要求，提出一种模糊推算定位（DR）算法.该算法在多层DR算法基础上，选取系统中有用实体属性对，并确定其相应隶属函数. 采用模糊一致关系从实体各属性间优先次序中得到其权值.通过模糊关联度计算在信息过滤过程中综合考虑实体属性，实现对任意两实体间相关性的衡量，计算结果被用来设置DR算法阈值.仿真结果表明，视角和实体大小属性均对信息过滤过程产生影响. 由该算法过滤后的运动轨迹符合人的感知特点.准确过滤率数据显示，该算法可平衡系统可扩展性要求和精度要求.     

HLA/RTI中DDM小模型的实现

该文简要介绍了HLA中DDM存在的必要性 ,之后从一般分布式的观点分析了HLA及DDM实现的原理 ,同时给出了存在DDM的情况下 ,HLA中数据公布和订购的基本流程。最后介绍了DDM已知的实现方法和我们的实现方法 ,同时详细地给出了对象属性和交互的请求应答机制。     

Shape Selective Chemistries with Modified Mordenite Zeolites

This is a review of work carried at Dow Chemical on the design and characterization of novel mordenite catalysts with a unique micro and meso-porous structure characterized by a variety of methods including, TEM, BET surface area and pore size distribution, and n-decane hydro-conversion. The catalytic performance of these catalysts in shape selective reactions is illustrated with results from n-decane hydro-conversion and applications to alkylation and trans-alkylation reactions of mono and polynuclear aromatic hydrocarbons and other chemistries. Juan M. Garcés and G. John Lee both retired from The Dow Chemical Company.     

Back to the future: digital decision making

The process of making decisions about the conception, design, development, deployment and regulation of complex information and communications technologies (ICT) systems with the potential to effect significant changes in society could be labelled ‘digital decision making’ (or DDM, for short). DDM is not the rational process that we might assume or wish it to be. It can even be difficult to define the boundaries of the social, political or technical environments to which the process applies. It depends on craft knowledge, power and agenda, politics and situational messiness, personal values, law and environment, and a host of other factors starkly illustrated by cases ranging from the Three Mile Island to the space shuttle Challenger disasters. Too often DDM leads to information systems failures, and it is time we started to learn from those past failures.