网格环境中跨异构域身份鉴别系统的研究与实现

针对跨异构域的身份鉴别问题进行研究,设计并实现了一个身份映射和信任证转换系统CredFed（Credential Federation）,解决了分别使用PKI和Kerberos作为鉴别机制的异构域之间身份鉴别的问题。CredFed是目前唯一在网格环境中解决此问题的系统。CredFed被设计为具有良好的互操作性和可扩展性的系统,使其不仅适用于网格环境,也适用于面向异构域的大规模分布式系统。该文对国内外相关工作作出了比较,简要地介绍了CredFed在CROWN网格安全平台中的应用并给出了实验结果对系统性能作出评估。     

一种基于P2P的非集中式网格资源发现方法

有效地发现网格的各种资源是影响网格整体性能的一个重要因素。针对资源发现在网格规模及应用不断扩展过程中变得越来越复杂的问题,在网格环境中融合Web Service技术,同时引入P2P思想,将资源发现模型分为内外两层,提出一个非集中式的网格资源发现方法,并应用于制造网格之中。实验证明,该模式有效解决了集中式模式带来的节点瓶颈等问题,并大幅降低分布式系统中资源发现产生的网络流量,具有高效性、可扩展性和鲁棒性。     

面向服务的织女星网格系统软件设计与评测

网格是开放的分布式系统,具有自治、动态和可扩展特性．在Internet环境下实现网格系统必须解决大规模资源共享与协同问题,也就是如何将Internet上无序的资源有序组织的问题．织女星网格系统软件针对现有网格平台软件存在的不足,借鉴传统计算机系统结构的方法来研究网格体系结构及其系统软件．面向网格应用的共性需求,提出了面向服务的层次化软件结构;引入网格资源空间的概念,实现了网格资源的虚拟化,屏蔽使用网格资源的技术细节．文章通过对网格关键问题的讨论,阐述了织女星网格系统软件的关键技术和设计思路,并通过对传统批作业的测试,分析了织女星网格系统软件的性能．     

实时分布式系统性能测试技术研究

实时分布式系统的性能是关注核心,对其进行评估和测试关系着系统的应用前景。基于实时分布式系统的性能测试需求,对系统关键的处理性能、存储性能、传输性能以及实时恢复性能这四种性能测试方法进行了研究和探讨,同时分别利用实时分布式系统中e600架构的处理器、flash存储器、FC网络以及分区调度策略针对这些方法开展了测试,并对获得的测试结果进行了分析。分析结果表明,性能测试结果可信,方法可行,可作为实时分布式系统评测依据。     

一种基于P2P机制的网格资源发现方法的研究

传统的网格资源发现系统采用集中式或者层次化的结构,但这些结构不能满足网格系统规模不断扩大的需求。而P2P系统是一种扩展性好的分布式系统,采用已有的P2P技术解决网格环境下的资源发现问题是一种有效的途径。简要介绍了目前采用P2P技术解决网格资源发现的问题,提出了一种采用超级节点模型和资源主动声明机制相结合的资源发现方法,并给出相应的算法描述,最后验证了其有效性。     

一种基于P2P机制的网格资源发现方法的研究

传统的网格资源发现系统采用集中式或者层次化的结构,但这些结构不能满足网格系统规模不断扩大的需求。而P2P系统是一种扩展性好的分布式系统,采用已有的P2P技术解决网格环境下的资源发现问题是一种有效的途径。简要介绍了目前采用P2P技术解决网格资源发现的问题,提出了一种采用超级节点模型和资源主动声明机制相结合的资源发现方法,并给出相应的算法描述,最后验证了其有效性。     

SIG框架基于多线程技术分布式系统的任务调度

空间信息网格是利用网格技术实现空间信息资源的共享、管理和提供空间信息服务的系统和各种的空问信息服务的基础设施,任务调度是分布式系统和网格系统最具有挑战的问题之一,Java语言里的多线程机制很好地解决了这一问题。该文主要研究了SIG中的任务调度技术,通过实验确定分布式系统里的线程数目,使系统性能获得局部最优。     

一种基于令牌的新的互斥算法分析与设计

在对现有典型分布式系统中互斥算法研究的基础上, 本文依据令牌技术, 提出了一种分布式系统中解决互斥问题的新算法.文中对算法的设计思想及实现过程进行了详细描述, 同时对其性能进行了严格的理论证明和分析, 该算法能有效地提高系统的通信效率.     

网格环境下的电子商务安全结构研究*

介绍了网格及其特点和网格中常用的安全技术、安全需求,基于OGSA安全体系结构和多级代理链的思想,给出了网格环境下的电子商务安全结构,并对其安全性能进行了评价和分析。     

COS:度量分布式大数据处理系统的效率

【目的】在大数据处理领域,分布式计算系统得到广泛应用,它们的可扩展性得到重点关注,但其绝对性能往往没有得到重视。我们希望提出科学合理、与时俱进的度量标准,对分布式系统的性能进行评估。【方法】本文通过对比特定任务的单机实现和分布式实现来讨论分布式系统的性能,提出COS(Configuration that Outperforms a Single machine)这一指标,来衡量分布式系统在达到单台机器的性能时,需要的硬件资源数量。我们选取k-means聚类和逻辑回归两个经典机器学习算法,对其进行单机多线程实现,并通过向量化计算、优化内存分配与访问等方式对性能进行了优化,为分布式多机系统的性能提供参考。【结果】以Apache Spark作为对标系统,实验发现无论是使用其原生编程接口,还是经过悉心优化的机器学习库,都要使用数倍甚至数百倍的机器,才能达到单机多线程实现的性能。【局限】分布式系统与单机实现进行性能对比并不是完全公平的,分布式系统的额外开销客观存在。【结论】但COS指标仍能反映分布式系统存在的绝对性能较差、没有充分利用硬件优势等问题。     

A new network epsilon-based DEA model for supply chain performance evaluation

Supply chain performance evaluation problems are inherently complex problems with multilayered internal linking activities and multiple entities. Data Envelopment Analysis (DEA) has been used to evaluate the relative performance of organizational units called Decision Making Units (DMUs). However, the conventional DEA models cannot take into consideration the complex nature of supply chains with internal linking activities. Network DEA models using radial measures of efficiency are used for supply chain performance evaluation problems. However, these models are not suitable for problems where radial and non-radial inputs and outputs must be considered simultaneously. DEA models using Epsilon-Based Measures (EBMs) of efficiency are proposed for a simultaneous consideration of radial and non-radial inputs and outputs. We extend the EBM model and propose a new Network EBM (NEBM) model. The proposed NEBM model combines the radial and non-radial measures of efficiency into a unified framework for solving network DEA problems. A case study is presented to exhibit the efficacy of the procedures and to demonstrate the applicability of the proposed method to a supply chain performance evaluation problem in the semiconductor industry.     

Application of optimal tracking to goal-seeking attack vehicles

In many important tactical situations, an attacking vehicle is guided toward a selected target by means of a control law selected to optimize a quadratic performance index. When this occurs, the tracking observer may take this intelligence into account and realize improvement in both the tracking accuracy and an estimate of the attacker's ultimate destination. An evaluation is given of Luenberger's proposed solution to problems of this type by determining for a missile analogy example the sensitivity of tracking performance to the tracker's knowledge of the attacker's intelligence parameters and by comparing the performance obtained using the proposed method with that provided by more conventional approaches that do not utilize a priori intelligence information. Conclusions regarding the practical implementation of the new approach are then drawn.     

A novel portable iris recognition system and usability evaluation

We propose a new portable iris recognition system. Because existing portable iris systems use customized embedded processing units, they are limited in ability to expand to other applications, and they have low processing power. To overcome such problems, we propose a new portable iris recognition system consisting of a conventional ultra-mobile personal computer (UMPC), a small universal serial bus (USB) iris camera, and near-infrared (NIR) light illuminators. In general, portable iris systems produce considerable optical blurring. Although auto-focusing motor-driven lenses can be used to overcome it, they are too bulky to be used in a small-sized portable iris system. Therefore, we adopt an iris image restoration algorithm which performs at real-time speed. And by using a conventional UMPC as a processing unit, our portable iris system is more extensible than previous systems. In general, the performance of iris recognition has been mainly evaluated based on the quantitative metrics such as EER (Equal Error Rate), ROC (Receiver Operational Characteristics) curve or recognition time. We propose a new performance measuring method based on qualitative metrics. That is usability evaluation including user acceptance, convenience, satisfaction and resistance.     

A novel hybrid genetic algorithm using local optimizer based on heuristic pattern move

A new hybrid genetic algorithm with the significant improvement of convergence performance is proposed in this study. This algorithm comes from the incorporation of a modified microgenetic algorithm with a local optimizer based on the heuristic pattern move. The hybridization process is implemented by replacing the two worst individuals in the offspring obtained from the conventional genetic operations with two new individuals generated from the local optimizer in each generation. Some implementation-related problems such as the selection of control parameters in the local optimizer are addressed in detail. This new algorithm has been examined using six benchmarking functions, and is compared with the conventional genetic algorithms without the local optimizer incorporated, as well as the hybrid algorithms incorporated with the hill-climbing method in terms of convergence performance. The results show that the proposed hybrid algorithm is more effective and efficient to obtain the global optimum. It takes about 6.4%-74.4% of the number of generations normally required by the conventional genetic algorithms to obtain the global optimum, while the computation cost for reproducing each new generation has hardly increased compared to the conventional genetic algorithms. Another advantage of this new algorithm is the implementation process is very simple and straightforward. There are no extra function evaluations and other complex calculations involved in the added local optimizer as well as in the hybridization process. This makes the new algorithm easy to be incorporated with the existing software packages of genetic algorithms so as to further improve their performance. As an engineering example, this new algorithm is applied for the detection of a crack in a composite plate, which demonstrates its effectiveness in solving engineering practical problems.     

关于互信息准则在分类(包括拒识类别)问题中的应用

不同于传统的基于性能为评价指标的机器学习方法, 基于互信息评价准则的学习方法显示出了独到的优越性. 但是, 如何理解互信息概念在分类问题中的具体内涵与应用特点仍然是不明确的. 本文推导了归一化互信息与包括拒识类别分类矩阵的显式表达关系. 给出了归一化互信息在极值情况下的三个相关定理, 以及在二值分类情况下误差敏感度分析方程. 为互信息与传统分类性能指标作出了初步理论方面解释. 通过给出的若干简单实例, 讨论了互信息概念及评价准则在分类问题中的基本应用特点及相关问题.     

工程监理人员绩效智能评价方法研究综述

工程监理制度是建造领域保障工程质量的重要抓手。监理人员是工程监理重要实施主体，对其 绩效的考核评价在保障监理工作及工程建设质量上具有重要意义。当前，有关研究仍以绩效考核的目标、内容 与流程为主，具体考核仍高度依赖人工手段，存在方法固化、单一，以及评价指标设定不合理、不明确等问题。 本研究旨在系统综述绩效评价方法与支撑性智能技术，提出智能绩效评价的新方向与新趋势。首先，从技术层 面和应用层面对于国内外的智慧监理技术下监理人员评价方法理论的研究和应用现状进行综述，介绍了涉及的 关键考核方法和评价指标理论的应用现状，并提炼了基于智慧化环境下的监理人员考评方法理论的应用情况。 在总结现况的基础上，对领域现存的问题和挑战做了讨论分析，针对监理人员绩效考核方法的简单化和更灵活、 客观的评价指标，结合现代综合指标评价方法结合人工智能、区块链技术等新型信息技术，提出了智慧化进程 下监理人员绩效考评方法理论的未来发展方向。     

A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers

This study presented a new performance evaluation method for tackling fuzzy multicriteria decision-making (MCDM) problems based on combining VIKOR and interval-valued fuzzy sets. The performance evaluation problem often exists in complex administrative processes in which multiple evaluation criteria, subjective/objective assessments and fuzzy conditions have to be taken into consideration simultaneously in management. Here, the subjective, imprecise, inexact and uncertain evaluation processes are modeled as fuzzy numbers by means of linguistic terms, as fuzzy theory can provide an appropriate tool to deal with such uncertainties. However, the presentation of linguistic expressions in the form of ordinary fuzzy sets is not clear enough [15] and [21]. Interval-valued fuzzy sets can provide more flexibility [4] and [14] to represent the imprecise/vague information that results, and it can also provide a more accurate modeling. This paper presents the interval-valued fuzzy VIKOR, which aims to solve MCDM problems in which the weights and performances of criteria are unequal by using the concepts of interval-valued fuzzy sets. A case study for evaluating the performances of three major intercity bus companies from an intercity public transport system is conducted to illustrate the effectiveness of the method.     

支持双拓扑结构的片上网络评估高层仿真平台

为实现高效的NoC（片上网络）性能评估, 缩短系统芯片的开发周期, 针对时钟精确级的NoC仿真方法进行研究, 提出了一种新型的高层次、高效率仿真平台, 与仅支持网格拓扑结构的传统仿真器相比, 其创新地支持了网格和环型双拓扑结构的性能评估, 同时支持虚通道扩展的路由器结构设计, 能快速得到网络的延迟、吞吐率、功耗等性能结果。实验结果表明, 该仿真平台能准确模拟NoC功能行为, 快速获得其仿真性能, 为NoC设计验证提供了高效的方法。     

Approximation of multiresponse deterministic engineering simulations: a dependent metamodeling approach

A new approach to metamodeling is introduced whereby a sequential technique is used to construct and simultaneously update mutually dependent metamodels for multiresponse, high-fidelity deterministic simulations. Unlike conventional approaches which produce a single metamodel for each scalar response independently, the present method uses the correlation among different simulation responses in the construction of the metamodel. These dependent metamodels are solved as a system of equations to estimate all individual responses simultaneously. Since several responses contribute to the construction of each individual metamodel, more information from the computed responses is used, thus improving the accuracy of the obtained metamodels. Examples are used to explore the relative performance of the proposed approach and show that the new approach outperforms conventional metamodeling approaches in terms of approximation accuracy. The new method should be particularly useful in problems that require very computationally intensive simulations.     

A comparative study of the improvement of performance using a PSO modified by ACO applied to TSP

Swarm-inspired optimization has become very popular in recent years. Particle swarm optimization (PSO) and Ant colony optimization (ACO) algorithms have attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving complex optimization problems. Both ACO and PSO were successfully applied for solving the traveling salesman problem (TSP). Performance of the conventional PSO algorithm for small problems with moderate dimensions and search space is very satisfactory. As the search, space gets more complex, conventional approaches tend to offer poor solutions. This paper presents a novel approach by introducing a PSO, which is modified by the ACO algorithm to improve the performance. The new hybrid method (PSO–ACO) is validated using the TSP benchmarks and the empirical results considering the completion time and the best length, illustrate that the proposed method is efficient.