基于业务规则的应急驱动虚拟组织模型设计

针对突发事件中出现的数据存储分布、格式异构等问题,借助于新的事件.条件一行动.角色.方法.工具(ECARMT)规则,提出并设计一个基于业务规则的应急驱动虚拟组织模型.该模型具有3个分层结构:资源层、服务组合层和应用层,能够对分布在异构平台的信息与服务进行动态组合,从而满足高效事件处置的要求.最后,实现了一个城市应急联动中心的应急值班调度原型系统.     

基于政务知识的服务集成模型和服务集成方法

分析电子政务应用集成发展的五个阶段以及当前面临的主要问题.针对电子政务领域应用的特殊性,提出了适合电子政务应用集成的知识本体模型,该模型具有基于规则推理和面向场景导航等特点.在服务集成模型的基础上,还提出一种服务集成方法.该方法通过场景导航、服务组合和服务调解等三个步骤实现Web服务的自动集成.利用该服务集成模型和方法可以有效解决传统服务集成模型在规则描述和推理能力方面、目标发掘方面以及服务自动组合能力上的不足.     

基于语义Web服务的业务过程集成的研究及实现

文中在分析目前业务过程集成所存在的问题(如缺乏统一描述、各系统之间缺乏语义等问题)的基础上,采用最新的语义Web服务技术设计了一种基于语义Web服务的业务过程集成模型,该模型不仅支持跨企业的业务合作,而且使在本领域内有共同的语义基础及业务过程规范,从而增强了企业间业务集成能力和协调能力。最后给出了一个简化的供应链上企业间业务过程集成的应用实例的设计与实现。     

一个基于元数据导航的服务工作流装配模型

以城市应急处置业务作为应用背景,提出了一个工作流的分层概念模型和一个与之关联的元数据分层描述规范,在此基础上构建了一个基于元数据导航的、从高层的业务应用到底层的分布、动态资源的逐层绑定的运行机制,基于该机制实现了一个城市应急联动系统IERS(Integrated Emergency Response System)的实验原型．该机制解决了从应急处置业务工作流到底层分布服务和资源的装配问题,增强了应急系统对动态、分布服务环境的支持力度,提高了应急处置业务在执行过程中的自动化水平和自适应性,同时也分解和简化了工作流问题的复杂度．     

基于语义Web服务的业务过程集成的研究及实现

文中在分析目前业务过程集成所存在的问题（如缺乏统一描述、各系统之间缺乏语义等问题）的基础上，采用最新的语义Web服务技术设计了一种基于语义Web服务的业务过程集成模型，该模型不仅支持跨企业的业务合作，而且使在本领域内有共同的语义基础及业务过程规范，从而增强了企业间业务集成能力和协调能力。最后给出了一个简化的供应链上企业间业务过程集成的应用实例的设计与实现。     

基于业务规则的Web服务整合

Web服务实现了Internet环境下企业应用的松散耦合与集成,使企业可以方便地集成现有的应用和部署新的应用。当前,已有不少Web服务整合模型提出,但大多忽视了业务规则在模型中的重要作用。为此提出了一个基于结构化的业务规则的Web服务整合模型来实现业务过程的动态整合,并将详细阐述整合模型所需的基本元素和结构化业务规则思想,以及Web服务整合的过程。     

Ad hoc网络中资源管理的研究

从资源管理在Ad hoc网络中的重要性出发,提出了一种分层式Ad hoc网络资源管理模型,该模型包括信息层、调度层和服务层,分别用来实现资源管理中的不同功能,并设计了一个资源调度模型,基于此调度模型可以实现资源申请、分析、检索、协调执行的一体化管理,同时给出了一种以资源应用服务为主、兼顾资源预留服务的资源调度的优化算法.     

一种跨边界业务过程集成平台

针对分布式异构环境下业务过程集成效率低、动态性差等问题,文章提出了一种跨边界业务过程集成模型,通过将跨边界业务过程集成模型构建为包含业务过程层、自治域内业务过程集成层以及跨边界业务过程集成层三个层次的层次模型,将每层问题简化,并通过层次间的紧密耦合解决复杂的实际问题。基于层次模型构建基于WebService的业务过程集成平台的体系结构,并利用业务过程动态协商技术,动态选择可提供个性化服务的服务提供者,按照合作双方协商结果进行实际业务过程集成,以提高跨边界业务过程集成的效率和动态适应能力。     

基于SOA企业应用集成框架研究与实现

通过深入分析传统的企业应用集成(EAI)优势与不足,将Web服务技术、SOA引入到EAI领域,提出了采用SOA模型的企业应用集成框架,并讨论了相关的支撑技术,给出了Web服务集成实现模型--网络通信层、消息传输层、服务描述层,服务发现层、服务保证层和服务组合层.为用户提供一个灵活;松耦合、跨平台、分布式、可扩展的基础集成服务平台.     

多层安全代理的集成访问控制系统架构研究

考虑到复杂的网络安全需要,将代理技术与其他安全机制相结合,通过运用多层安全代理和集成访问控制技术,架构了一个基于多层安全代理的集成访问控制模型.在这种架构下,实现了基于角色访问控制开发的校园网认证系统.该模型具有多层安全代理能够自适应调度、灵活的访问规则和智能的网络安全防范等主要特点.     

基于YARN的分布式资源动态调度与协同分配系统

Storm on YARN是目前主流的分布式资源调度框架,但其存在需要人工干预和无法根据资源可用性实时调整系统资源的不足。根据流数据处理的实时延迟计算系统负载情况,在Storm平台上基于YARN设计分布式资源调度和协同分配系统。建立包含系统层和任务层的双层调度模型,系统层通过对流数据处理负载的实时监测进行资源分配预测,任务层利用ZooKeeper和YARN对集群资源的高效管理能力进行动态资源管理。实验结果表明,该系统可以实时调整集群资源分布,有效减小系统延迟。     

Energy-aware scheduling and simulation methodologies for parallel security processors with multiple voltage domains

Dynamic voltage scaling (DVS) and power gating (PG) have become mainstream technologies for low-power optimization in recent years. One issue that remains to be solved is integrating these techniques in correlated domains operating with multiple voltages. This article addresses the problem of power-aware task scheduling on a scalable cryptographic processor that is designed as a heterogeneous and distributed system-on-a-chip, with the aim of effectively integrating DVS, PG, and the scheduling of resources in multiple voltage domains (MVD) to achieve low energy consumption. Our approach uses an analytic model as the basis for estimating the performance and energy requirements between different domains and addressing the scheduling issues for correlated resources in systems. We also present the results of performance and energy simulations from transaction-level models of our security processors in a variety of system configurations. The prototype experiments show that our proposed methods yield significant energy reductions. The proposed techniques will be useful for implementing DVS and PG in domains with multiple correlated resources.     

Extended event–condition–action rules and fuzzy Petri nets based exception handling for workflow management

Exception handling plays a key role in dynamic workflow management that enables streamlined business processes. Handling application-specific exceptions is a knowledge-intensive process involving different decision-making strategies and a variety of knowledge, especially much fuzzy knowledge. Current efforts in workflow exception management are not adequate to support the knowledge-based exception handling. This paper proposes a hybrid exception handling approach based on two extended knowledge models, i.e., generalized fuzzy event–condition–action (GFECA) rule and typed fuzzy Petri net extended by process knowledge (TFPN-PK). The approach realizes integrated representation and reasoning of fuzzy and non-fuzzy knowledge as well as specific application domain knowledge and workflow process knowledge. In addition, it supports two handling strategies, i.e., direct decision and analysis-based decision, during exception management. The approach fills in the gaps in existing related researches, i.e., only providing the capability of direct exception handling and neglecting fuzzy knowledge. Based on TFPN-PK, a weighted fuzzy reasoning algorithm is designed to address the reasoning problem of uncertain goal propositions and known goal concepts by combining forward reasoning with backward reasoning and therefore to facilitate cause analysis and handling of workflow exceptions. A prototype system is developed to implement the proposed approach.     

A concurrent rule scheduling algorithm for active rules

The use of rules in a distributed environment creates new challenges for the development of active rule execution models. In particular, since a single event can trigger multiple rules that execute over distributed sources of data, it is important to make use of concurrent rule execution whenever possible. This paper presents the details of the integration rule scheduling (IRS) algorithm. Integration rules are active database rules that are used for component integration in a distributed environment. The IRS algorithm identifies rule conflicts for multiple rules triggered by the same event through static, compile-time analysis of the read and write sets of each rule. A unique aspect of the algorithm is that the conflict analysis includes the effects of nested rule execution that occurs as a result of using an execution model with an immediate coupling mode. The algorithm therefore identifies conflicts that may occur as a result of the concurrent execution of different rule triggering sequences. The rules are then formed into a priority graph before execution, defining the order in which rules triggered by the same event should be processed. Rules with the same priority can be executed concurrently. The IRS algorithm guarantees confluence in the final state of the rule execution. The IRS algorithm is applicable for rule scheduling in both distributed and centralized rule execution environments.     

苏州城区活水联控联调系统架构设计

苏州城区河道纵横,闸、泵、堰等水利控制工程众多,目前主要依赖人工调度的模式,统筹兼顾难度较大,难以满足苏州城区水环境高质量目标实现所需的精准化调度要求。分析城区水利工程、监测设备及信息化建设现状,以畅流活水智慧调度应用开发为出发点,以监测数据为驱动,以模型为核心,以远控为手段,依托模型云,构建包括监测设备层、支撑平台层和业务应用层的苏州城区活水联控联调系统平台。平台建成后,利用物联感知系统代替人工观测,实现全智能一键化精准调度代替人工调度,充分发挥清水工程效益,通过精准调度可实现重点河道水体清澈,提升苏州市城区水利综合调度决策能力,完善苏州水利信息化建设布局。     

突发公共卫生事件的应急响应服务系统的分析与设计

阐述了贵州省疾病控制和预防中心目前阶段的工作成绩和存在的问题。在此基础上,设计了基于传染病学时空传播模型的突发公共卫生事件的应急响应服务系统。系统通过以事件驱动的服务动态整合机制,联合调度分布式的多种信息资源,进行多部门协同办案,为公共安全应急管理体系的建设提供了良好的技术支撑。     

Reputation-based dependable scheduling of workflow applications in Peer-to-Peer Grids

Grids facilitate creation of wide-area collaborative environment for sharing computing or storage resources and various applications. Inter-connecting distributed Grid sites through peer-to-peer routing and information dissemination structure (also known as Peer-to-Peer Grids) is essential to avoid the problems of scheduling efficiency bottleneck and single point of failure in the centralized or hierarchical scheduling approaches. On the other hand, uncertainty and unreliability are facts in distributed infrastructures such as Peer-to-Peer Grids, which are triggered by multiple factors including scale, dynamism, failures, and incomplete global knowledge.In this paper, a reputation-based Grid workflow scheduling technique is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Peer-to-Peer Grid environments. The proposed approach builds upon structured peer-to-peer indexing and networking techniques to create a scalable wide-area overlay of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers mediated via Grid resource brokers. The proposed algorithm dynamically adapts to changing resource conditions and offers significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. The results evaluated through an extensive trace driven simulation show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.     

保险协同商务框架

协同应用是一个虚拟集成的资源分布式网络，通过共享在各自领域的知识和专长，致力于解决某一特定的商务问题或完成某一特定的工作，初步研究了协同应用及其特征，分析了多种协同应用，总结了协同应用的平台式架构模型，提出了将协同应用于保险公司电子商务系统的设想，在深入分析保险业务模型的基础上，对保险协同商务应用进行了框架设计。     

Neural network‐based multi‐agent approach for scheduling in distributed systems

A distributed system consists of a collection of autonomous heterogeneous resources that provide resource sharing and a common platform for running parallel compute‐intensive applications. The different application characteristics combined with the heterogeneity and performance variations of the distributed system make it difficult to find the optimal set of needed resources. When deployed, user applications are usually handled by application domain experts or system administrators who depending on the infrastructure provide a scheduling strategy for selecting the best candidate resource over a set of available resources. However, the provided strategy is usually generic, aimed at handling a wide array of applications and does not take into consideration specific application resource requirements. As such, an intelligent method for selecting the best resources based on expert knowledge is needed. In this paper, we propose a neural network‐based multi‐agent resource selection technique capable of mimicking the services of an expert user. In addition, to cope with the geographical distribution of the underlying system, we employ a multi‐agent coordination mechanism. The proposed neural network‐based scheduling framework combined with the multi‐agent intelligence is a unique approach to efficiently deal with the resource selection problem. Results run on a simulated environment show the efficiency of our proposed method. Several scheduling simulations were conducted to compare the performance of some conventional resource selection methods against the proposed agent‐based neural network technique. The results obtained indicate that the agent‐based approach outperformed the classical algorithms by reducing the amount of time required to search for suitable resources irrespective of the resource size. Copyright © 2016 John Wiley & Sons, Ltd.     

一种MAS构件知识复用动态演化模型

为提高企业的知识利用效率,增强企业创新能力,针对企业现有知识和系统,提出将企业知识管理的业务逻辑与知识处理事务分开,建立了基于多智能体和构件知识的知识复用模型,设计了知识管理业务逻辑的规则模型和智能体的活动行为模型,讨论了基于多智能体的规则协调模式,有效地支持知识的动态复用和知识使用过程的动态重组,增强知识管理系统的分布式处理能力和规模可扩展能力.在分布式构件库系统中,智能体通过协作联合完成任务要求.每个智能体拥有自己的知识库,并且具备学习能力,能够更新其知识库以保持执行结果的有效性.