Design of Low-Bandwidth Spatially Distributed Feedback

The paper considers a family of linear time-invariant and spatially invariant (LTSI) systems that are both distributed and localized. The spatial responses of the distributed plant are localized in spatial neighborhoods of each location. The feedback computations are also distributed and the information flow is localized in a spatial neighborhood of each location. The feedback is aimed at controlling spatial distributions of variables in the systems with a relatively low bandwidth in the time direction. Such systems have many important applications including industrial processes, imaging systems, signal and image processing, and others. We describe a new method for designing (tuning) a certain family of low-bandwidth controllers for such plants. We consider LTSI controllers with a fixed structure, which is a PID or a similar low-bandwidth feedback in time and local in spatial coordinates. Two spatial feedback filters, symmetric and with finite spatial response, modify the local PID control signal by mixing in the error and control signals at nearby nodes. These two filters provide loopshaping and regularization of the spatial feedback loop. Like an ordinary PID controller, this controller structure is simple, but provides adequate performance in many practical settings. We cast a variety of specifications on the steady-state spatial response of the controller and its time response as a set of linear inequalities on the design variables, and so can carry out the design of the spatial filters using linear programming. The method handles steady-state limits on actuator signals, error signals, and several constraints related to robustness to plant and controller variation. The method allows handling the effects of boundary conditions and guaranteed closed-loop spatial or time decay. It does appear to work very well for low-bandwidth controllers, and so is applicable in a variety of practical situations.      

On the Stability of Spatially Distributed Systems

In this note, a sufficient condition is derived for the stability of a spatially invariant distributed dynamical system, based on the geometrical structure of the null space of a matrix polynomial. This condition is less conservative than the available computationally feasible criteria. Moreover, using the idea of parameter dependent linear matrix inequalities, a necessary and sufficient condition is obtained. Both of these two conditions are expressed by LMIs. While the necessity of the latter is lost if the degree of the related matrix polynomials is small, its conservativeness can be sequentially reduced.      

An Evolutionary Model of Endogenous Business Cycles

In this paper, we present an evolutionary model of industry dynamics yielding endogenous business cycles with ‘Keynesian’ features. The model describes an economy composed of firms and consumers/workers. Firms belong to two industries. The first one performs R&D and produces heterogeneous machine tools. Firms in the second industry invest in new machines and produce a homogenous consumption good. Consumers sell their labor and fully consume their income. In line with the empirical literature on investment patterns, we assume that the investment decisions by firms are lumpy and constrained by their financial structures. Moreover, drawing from behavioral theories of the firm, we assume boundedly rational expectation formation. Simulation results show that the model is able to deliver self-sustaining patterns of growth characterized by the presence of endogenous business cycles. The model can also replicate the most important stylized facts concerning micro- and macro-economic dynamics. Indeed, we find that investment is more volatile than GDP; consumption is less volatile than GDP; investment, consumption and change in stocks are procyclical and coincident variables; employment is procyclical; unemployment rate is anticyclical; firm size distributions are skewed but depart from log-normality; firm growth distributions are tent-shaped. JEL Classifications: C15, C22, C49, E17, E22, E32.     

基于云模型的进化算法

基于云模型在非规范知识的定性、定量表示及其相互转换过程中的优良特征,结合进化计算的基本思想,提出一种基于云模型的进化算法.该算法利用云模型对物种的遗传变异进化统一建模,能够自适应控制遗传变异的程度和搜索空间的范围,从而可以快速收敛到最优解,较好地避免了传统遗传算法易陷入局部最优解和选择压力过大造成的早熟收敛等问题.仿真结果表明:该算法具有精度高、收敛速度快等优点.云模型和进化计算思想的有效结合一方面拓宽了云模型的应用领域,也为进化计算的研究进行了新的探索和尝试.     

一种分布式告警融合模型的分析

为解决IDS产生大量相似的或无用的告警信息的问题,需要应用告警融合技术对告警信息进行处理。在已有的算法基础上设计了一种告警合成算法。有效地减少了无用警报的数量,又保持了警报处理的及时性,为后期的关联工作做好了准备。     

An Availability Model for Distributed Transaction Systems

A method is proposed for quantitatively evaluating the availability of a distributed transaction system (DTS). The DTS dynamics can be modeled as a Markov process. The problem of formulating the set of linear homogeneous equations is considered, obtaining the related coefficient matrix, that is, the transition rate matrices of the DTS elements. Such operations can be performed according to the rules of Kronecker algebra. The transition rate matrices are used to calculate the probabilities of the different possible states of the DTS. The availability with respect to a transaction T is computed through its representation by means of a structure graph and a structure vector related to the probabilistic state of the DTS element relevant to the transaction T itself.     

一个基于对象的分布式多媒体系统模型

提出了一个基于对象的分布式多媒体系统模型。由媒体存取层、多媒体对象层和多媒体表现层等构成的层次模型将媒体异构环境存取、分布式多媒体对象处理和语义合成表现等问题在不同层次分别进行处理,并能够全面处理多种时序关系以及ＱｏＳ（ｑｕａｌｉｔｙ ｏｆ ｓｅｒｖｉｃｅ）等特殊问题。     

An Adaptive Tradeoff Model for Constrained Evolutionary Optimization

In this paper, an adaptive tradeoff model (ATM) is proposed for constrained evolutionary optimization. In this model, three main issues are considered: (1) the evaluation of infeasible solutions when the population contains only infeasible individuals; (2) balancing feasible and infeasible solutions when the population consists of a combination of feasible and infeasible individuals; and (3) the selection of feasible solutions when the population is composed of feasible individuals only. These issues are addressed in this paper by designing different tradeoff schemes during different stages of a search process to obtain an appropriate tradeoff between objective function and constraint violations. In addition, a simple evolutionary strategy (ES) is used as the search engine. By integrating ATM with ES, a generic constrained optimization evolutionary algorithm (ATMES) is derived. The new method is tested on 13 well-known benchmark test functions, and the empirical results suggest that it outperforms or performs similarly to other state-of-the-art techniques referred to in this paper in terms of the quality of the resulting solutions.     

An Asynchronous Communication Model for Distributed Concurrent Objects

Distributed systems are often modeled by objects that run concurrently, each with its own processor, and communicate by synchronous remote method calls. This may be satisfactory for tightly coupled systems, but in the distributed setting synchronous external calls lead to much waiting; at best resulting in inefficient use of processor capacity, at worst resulting in deadlock. Furthermore, it is difficult to combine active and passive behavior in concurrent objects. This paper proposes an object-oriented solution to these problems by means of asynchronous method calls and conditional processor release points. Although at the cost of additional internal nondeterminism in the objects, this approach seems attractive in asynchronous or unreliable environments. The concepts are integrated in a small object-oriented language with an operational semantics defined in rewriting logic, and illustrated by examples. This paper extends and combines results which have appeared in the proceedings of the 2004 International Conference on Software Engineering and Formal Methods (SEFM) [37] and the 2004 International Workshop on Rewriting Logic and its Applications (WRLA) [41].     

多Agent分布仿真中的环境划分模型

在多Agent分布仿真中,采用分布式环境模型有利于提高系统的扩展性.把分布式环境模型划分到多机上执行需要考虑计算和通信两方面的代价,求解总代价最小的划分方案的问题是NP难的,且当P≠NP时不存在具有有限近似比率的多项式时间复杂性近似算法.提出了一种基于准贪心策略和分而治之思想的近似算法;分析了算法的时间复杂性;评测验证了近似算法的有效性.     

An Adaptive Programming Model for Fault-Tolerant Distributed Computing

The capability of dynamically adapting to distinct runtime conditions is an important issue when designing distributed systems where negotiated quality of service (QoS) cannot always be delivered between processes. Providing fault tolerance for such dynamic environments is a challenging task. Considering such a context, this paper proposes an adaptive programming model for fault-tolerant distributed computing, which provides upper-layer applications with process state information according to the current system synchrony (or QoS). The underlying system model is hybrid, composed by a synchronous part (where there are time bounds on processing speed and message delay) and an asynchronous part (where there is no time bound). However, such a composition can vary over time, and, in particular, the system may become totally asynchronous (e.g., when the underlying system QoS degrade) or totally synchronous. Moreover, processes are not required to share the same view of the system synchrony at a given time. To illustrate what can be done in this programming model and how to use it, the consensus problem is taken as a benchmark problem. This paper also presents an implementation of the model that relies on a negotiated quality of service (QoS) for communication channels     

分布式交互媒体的一种应用控制模型

讨论了分布式交互媒体的特性和各种应用控制模型,并提出了一种新的控制模型——混合式控制模型,该模型可以有效的减轻最大平均操作时延,减轻服务器负担和用户应用程序复杂度,提高扩展性。     

An Optimal Model and Algorithm of Distributed Information System

Distributed information system makes itself be placed in changing file storage position according to the users＇ request pattern. In this paper, we rebuild the model for a management system to turn the process of file managing into a 0-1 programming problem, and present a new individual form to improve the operating efficiency. Aiming at the model, we define a neighborhood span to make segmentation for searching space by using the fitness, based on the region contraction algorithm, present a new evolution algorithm which has the capability of self-adaptively generating new individuals, and ultimately solve the management problem of the distributed file system.     

一种基于SOAP的实现异种分布式组件互操作的方法

分析了现今流行的分布式组件技术,指出了在Internet环境下这些分布式组件技术在互操作性方面的不足,进而提出了一种基于SOAP的实现异种分布式组件互操作的方法,并且给出了在EJB Server上的具体实现方案。最后,讨论了该方法在今后的进一步的研究重点。     

一种在开发时实现分布式仿真系统通信协议的异构方案

分布式仿真系统通信协议的异构是解决不同协议下仿真资源重用的关键,也是近几年仿真领域研究的热点之一.设计了一种在仿真系统开发阶段实现通信协议异构的方案,该方案的重点是实现一个与通信协议无关的开发包,从实例连接、对象管理、事件管理和公共接口四个方面讨论了该开发包的基本原型.对比运行时的异构方案,分析了该方案的特点,指出开发...     

一种基于多Agent的分布式入侵检测系统设计

在分析现有基于Agent的入侵检测系统的基础上,提出了一种基于多Agent分布式入侵检测系统模型。该模型采用了分布检测、分布响应的模式,各Agent之间具有良好的相对独立性。通过多Agent技术的思想建立系统总体结构,给出了模型的各个组成部分,并对结构中各种Agent与中心控制台的功能设计进行了分析。同时对涉及到特征匹配算法、动态选举算法、协同算法进行了初步的设计与分析。系统可充分利用各Agent的协同完成入侵检测任务,实时响应,可有效地改进传统IDS。     

An Information-Based Model for Failure-Handling in Distributed Database Systems

We consider the failure atomicity problem of distributed transactions in conjunction with the maximization of database availability. We propose a new information-based model for the distributed transaction-execution, which explicitly expresses the information at each stage during a protocol. In addition to rederiving certain existing results, we prove a fundamental relation among the site failures and the network partitioning. We propose a realistic model for site failures under which we show that the costs of commit and termination protocols can be greatly reduced. Finally, we explore the possible recovery strategies for a failed site and show how they are improved under our site failure model.     

可扩展自适应的分布对象容错模型研究

容错技术是实现分布对象系统可靠性的一种重要手段.现有的分布对象容错系统在保证应用程序可靠性的同时,却对其性能造成很大影响.一方面,这是由于系统缺乏应用的语义信息,只能采用少数几种保守的容错策略;另一方面是因为系统缺乏自适应性,导致资源利用率较低.为了解决这些问题,提出了一种具有可扩展性和自适应性的分布对象容错模型,它允许容错应用开发者扩充新的容错策略,并且在系统运行环境变化发生改变时,能够动态地调整配置结构,从而显著地改善容错应用程序的性能.     

一种基于演化自治代理的入侵检测系统模型

针对当今网络检测系统在安全性和有效性方面存在的问题,提出了一个基于演化自治代理的入侵检测系统模型。由于该模型所基于的代理具有演化性和自治性,所以具有安全有效和耗用资源少等特点。     

基于演化算法实现多目标优化的岛屿迁徙模型

多目标演化算法(MOEA)利用种群策略，尽可能地找出多目标问题的Pareto最优集供决策者选择，为决策者提供了更大的选择余地，与其它传统的方法相比有了很大的改进．但提供大量选择的同时，存在着不能为决策者提供一定的指导性信息，不能反映决策者的偏好，可扩展性差等问题．本文提出了一个新的多目标演化算法(MOEA)计算模型…岛屿迁徙模型，该模型体现了一种全新的多目标演化优化的求解思想，对多目标优化问题的最优解集作了新的定义．数值试验结果表明，岛屿迁徙模型在求解MOP时有效地解决了以上问题，并且存在进一步改进的潜力．