状态驱动的可执行业务流程模型的设计与实现

在企业间的流程协同过程中,为了使企业的业务规则管理更灵活,防止企业私有的业务规则暴露给其他企业,并有效地监控流程的执行过程,将业务规则库和Web服务有机地整合,构建状态驱动的可执行业务流程模型（SEBPM）。通过定义抽象业务流和扩展的业务规则,得出业务规则和过程流之间的耦合策略。给出一个SEBPM的具体应用实例。     

一种面向业务规则和流程的推理引擎架构

目前基于业务流程模型控制规则引擎的工作流引擎已经开始提倡使用。针对这种情况,基于BPMN业务流程模型的工作流引擎,提出一种适用于业务流程模型和规则集成与执行的推理引擎架构。该架构引入XTT2的规则表示,集成了jBPM工作流管理系统和HeaRT规则引擎,由工作流引擎控制专用规则推理引擎执行规则决策表运行。原型实现表明了该架构可实现规则任务的可视化设计,并支持对得到的规则任务模型的形式验证。     

基于SOA的业务规则代理研究

针对业务规则领域存在的问题,分析规则引擎主要的实现技术与规范以及基于SOA规则引擎的优越性,提出基于SOA的规则引擎代理。该结构能屏蔽不同业务规则引擎之间的异构性,向客户端提供统一的Web服务接口来执行不同规则引擎的规则。给出应用于移动公司的具体实例。     

基于可配置规则的BOM视图转换方法

在确保物料清单(bill of material,BOM)多视图之间产品数据一致性和完整性的前提下,为实现BOM视图转换技术能够满足企业业务规则的个性化需求并适应企业业务规则可能发生的改变,提出了基于可配置规则的BOM视图转换方法.在分析企业中各种BOM视图之间关系的基础上,建立了BOM视图及其转换过程的基础模型,给出了装配转换规则的结构定义及其配置方法,通过实际案例介绍了该方法在BOM视图转换过程中的应用,表明了该方法能够满足企业业务规则的个性化需求并适应企业业务规则的变化.     

基于SOA的供应链管理平台设计与实现

为解决供应链中因各类差异性问题导致的异构系统集成困难,提出了一种基于面向服务体系架构的供应链管理平台,设计了由业务流程开发平台、业务执行平台和IT资源集成层组成的三层平台体系架构,给出了管理平台中最为核心的业务执行引擎和企业服务总线体系及工作原理.将管理平台应用于以摩托车整车装配企业为核心的供应链集成管理中,有效降低了供应链中各异构系统之间业务整合与数据整合难度,表明了该平台的有效性与可拓展性.     

异构应用系统业务协同工作流平台设计与实现

针对电子政务中异构应用系统之间的业务协同问题,设计并实现了异构应用系统业务协同工作流服务平台原型系统.该系统可根据不同部门业务协同的需求,使用可视化建模工具,按照流程驱动方式将异构应用系统整合在一起,实现业务流程管理与应用系统间的松散耦合,并在企业养老金发放业务协同中进行了应用.     

SOA的企业实践从何而起

SOA之于企业,无论有多少种产品和解决方案,具体到每一个企业来说,最根本的需求是对企业内部的业务和流程的重构。SOA为企业所能带来的价值,就是基于其内部统一的数据交互接口、将业务分解为独立的模块成为服务、提供统一的服务接口,这样的思想所带来的是能够让企业的IT系统根据业务需求的变化而迅速改进。服务构造的过程,也就是对企业业务流程的分解、     

产业链协同SaaS平台业务流程定制安全技术研究

针对产业链协同SaaS平台企业群以盟主企业为核心的业务流定制过程中的流程规则编排、存储/访问以及执行控制3个环节可能存在的安全隐患,建立了基于数字签名及业务实例关联的业务流程安全控制模型,对XML数字签名和验证模式、存储策略及模型执行策略进行了研究,提出了基于用户身份认证和业务实例关联的安全签名、存储和执行算法。对该安全模型和算法在汽车产业链协同SaaS平台企业群车辆售后的三包业务流程定制和执行过程进行了验证,结果表明其能防止业务流程在编排、存储和执行过程中被非法篡改和调用。     

基于Artifact的流程设计平台

基于jBPM的业务流程是面向过程的,不方便业务人员对信息的提取、分析。所以,以数据为中心的流程管理技术就应运而生。Artifact是记录业务流程的数据实体,围绕Artifact的业务流程管理正在成为业务流程管理研究的一个热点。jBPM流程能够很好的描述业务流程,为其提供分析、实施的基础。把Artifact的业务流程管理技术和jBPM的业务流程管理技术结合在一起,可以为系统模型的设计和实现提供方便同时为代码自动生成提供参考基础,体现了敏捷开发的思想。     

模型驱动的业务流程执行方法研究

模型驱动体系结构对于增强业务流程管理系统的模型重用性和软件开发效率有重要作用.以往研究主要集中于MDA在流程建立阶段的作用,目的是介绍模型驱动方法在流程执行阶段的应用.采用构造基于XML Schema的业务流程集成元模型,包括过程、业务数据和组织机构三方面,再基于元模型建立易于扩展和重用的平台无关模型,最后按映射规则生成代码组件、SQL语句和用户界面,并由三种模型的逻辑关系得到业务流程执行元模型的框架.实践结果表明基于XML的业务流程模型能方便地转换为可执行的程序组件,并能在业务流程引擎的协调下有效运行.模型驱动方法能有效地运用在业务流程的执行阶段,下一步的研究重点是业务流程引擎代码框架的映射规则定义以及MDA在业务流程仿真中的应用实现.     

A systematic approach to business process reengineering

In this study, a business process is defined as a set of various tasks which are closely inter-related and is assumed to have its own objectives to achieve. A set of processes constitute a business system. Many business process reengineering plans turned out to be unsuccessful because they are based on the existing process which assumed tasks along the process independent or based on the assumption that a process is independent of other processes. This approach generated redundant tasks or led to conflict between business processes. Under this approach, it very difficult to predict the result of the plan due to localized analysis of the process. To avoid aforementioned problems, a systematic, analytic and iterative approach to build up a master plan for business process reengineering is proposed.     

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。     

A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management

The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment. However, while collaborative business expands the realm of businesses, it also causes various hazards in collaborative Interaction, such as data falsification, inconstancy, and misuse. To solve these issues, a blockchain-based collaborative business modeling approach was proposed and analyzed. However, the existing studies lack the blockchain risk problem-solving specification, and there is no verification technique to examine the process. Consequently, it is difficult to confirm the appropriateness of the approach. Thus, here, we propose and build a blockchain-based trust model to strengthen and verify the integrity and security of the collaborative business process; Integrity and security address the validity of collaborative interactions in terms of a trust, and we construct a blockchain pattern based on trust elements to meet the required the characteristics. Specifically, a trust model can be applied to the healthcare data-sharing process, and then the achievement of the trust-based safe data-sharing process can be proven. Our model can be used as a trust-building guidance tool or for integrity and security verification with the collaborative business process in a distributed environment with blockchain.     

Incorporating structural improvement into resource allocation for business process execution planning

Resource management has been recognised as an important topic for business process execution for a long time. Most existing works on resource allocation for business processes simply assume that the structure of a business process is always fixed, and therefore do not discuss the possibility of optimising resource allocation by adapting process structures to actual resource situations. To fill this gap, we propose a resource optimisation approach of improving process structures according to resource situations and thereby pursuing the best resource utilisation efficiency. This approach comprises a role‐based business process model for resource allocation and the strategies for optimising resource allocation in conjunction with a business process improvement. A set of heuristic rules are established to guide the resource allocation for the purposes of preventing resource conflicts, shortening the total execution time, minimising the total cost, etc. Particular algorithms are also developed to implement the resource allocation according to these rules. In addition, an experimental study is conducted to discuss the incorporation of business process improvement into resource allocation for optimal process execution. Copyright © 2012 John Wiley & Sons, Ltd.     

Pattern-driven green adaptation of process-based applications and their runtime infrastructure

Business processes are a key aspect of modern organization. In recent years, business process management and optimization has been applied to different cross-cutting concerns such as security, compliance, or Green IT, for example. Based on the ecological characteristics of a business process, proper environmentally sustainable adaptation strategies can be chosen to improve the total environmental impact of the business process. We use ecological sustainable adaptation strategies that are described as green business process patterns. The application of such a green business process pattern, however, affects the business process layer, the application component and the infrastructure layer. This implies that changes in the application infrastructure also need to be considered. Hence, we use best practices of cloud application architectures which are described as Cloud patterns. To guide developers through the adaptation process we propose a pattern-based approach in this work. We correlate Cloud patterns relevant for sustainable business processes to green business process patterns and organize them within a classification. To provide concrete implementation support we further annotate these Cloud patterns to application component models that are described with the topology and orchestration specification for cloud applications (TOSCA). Using these annotations, we describe a method that provides the means to optimize business processes based on green business process patterns through adapting the implementation of application components with concrete TOSCA implementation models.     

A novel completeness definition of event logs and corresponding generation algorithm

As the promotion of technologies and applications of Big Data, the research of business process management (BPM) has gradually deepened to consider the impacts and challenges of big business data on existing BPM technologies. Recently, parallel business process mining (e.g. discovering business models from business visual data, integrating runtime business data with interactive business process monitoring visualisation systems and summarising and visualising historical business data for further analysis, etc.) and multi-perspective business data analytics (e.g. pattern detecting, decision-making and process behaviour predicting, etc.) have been intensively studied considering the steep increase in business data size and type. However, comprehensive and in-depth testing is needed to ensure their quality. Testing based solely on existing business processes and their system logs is far from sufficient. Large-scale randomly generated models and corresponding complete logs should be used in testing. To test parallel algorithms for discovering process models, different log completeness and generation algorithms were proposed. However, they suffer from either state space explosion or non-full-covering task dependencies problem. Besides, most existing generation algorithms rely on random executing strategy, which leads to low and unstable efficiency. In this paper, we propose a novel log completeness type, that is, #TAR completeness, as well as its generation algorithm. The experimental results based on a series of randomly generated process models show that the #TAR complete logs outperform the state-of-the-art ones with lower capacity, fuller dependencies covering and higher generating efficiency.     

Generating optimized configurable business process models in scenarios subject to uncertainty

ContextThe quality of business process models (i.e., software artifacts that capture the relations between the organizational units of a business) is essential for enhancing the management of business processes. However, such modeling is typically carried out manually. This is already challenging and time consuming when (1) input uncertainty exists, (2) activities are related, and (3) resource allocation has to be considered. When including optimization requirements regarding flexibility and robustness it becomes even more complicated potentially resulting into non-optimized models, errors, and lack of flexibility.ObjectiveTo facilitate the human work and to improve the resulting models in scenarios subject to uncertainty, we propose a software-supported approach for automatically creating configurable business process models from declarative specifications considering all the aforementioned requirements.MethodFirst, the scenario is modeled through a declarative language which allows the analysts to specify its variability and uncertainty. Thereafter, a set of optimized enactment plans (each one representing a potential execution alternative) are generated from such a model considering the input uncertainty. Finally, to deal with this uncertainty during run-time, a flexible configurable business process model is created from these plans.ResultsTo validate the proposed approach, we conduct a case study based on a real business which is subject to uncertainty. Results indicate that our approach improves the actual performance of the business and that the generated models support most of the uncertainty inherent to the business.ConclusionsThe proposed approach automatically selects the best part of the variability of a declarative specification. Unlike existing approaches, our approach considers input uncertainty, the optimization of multiple objective functions, as well as the resource and the control-flow perspectives. However, our approach also presents a few limitations: (1) it is focused on the control-flow and the data perspective is only partially addressed and (2) model attributes need to be estimated.     

业务过程协同中数据恢复策略建模及分析

业务过程协同允许组织之间彼此进行通信,交互和协作以完成特定的业务目标。为了确保实施的正确性和一致性,需要对业务过程协同进行建模和分析,但现有的工作鲜有关注于从架构的视角和数据的层次来对其进行讨论。为此,首先提出了一种“代理端 盟主端”业务过程协同架构;其次,通过对该协同架构进行分析,提出了一种业务过程协同的数据恢复通用模型;最后,基于该通用模型,提出了数据恢复策略模型,以此为基础提出了五种数据恢复策略并采用随机Petri网对其进行建模与仿真。实验结果表明,采用最短队列随机恢复策略能够使得业务过程协同应用在协同中确保高的系统吞吐量、快的响应时间及低的拒绝率。     

协同业务过程与需求的建模及一致性验证

自底向上建模方法中的业务过程由不同组织开发,无法在设计阶段就预见其潜在的所有交互可能.因此,在实际协作中,建立协同业务过程可能与参与组织期望的系统功能和特性不一致.为此,提出一种协同业务过程与需求的建模及一致性验证方法.首先,引入并发操作符,提供一种通过组合参与组织的业务过程构建协同业务过程方法;然后,扩展目标模型,提出需求依赖图来建模参与组织的需求;最后,基于模型检测技术提出协同业务过程与需求一致性检测方法.重点解决了将协同业务过程转换为表达能力相同FSP进程规约和参与组织需求转换为LTL公式这两个问题.通过对典型的协同业务过程集阐述提出方法的有效性,并对方法分析效率进行评价,结果表明：相对已有工作,提出方法能够更加有效地用于协同业务过程与需求的一致性分析.     

Adaptive integration activity management for on demand business process collaboration

Today businesses are interacting and collaborating more often in the context of a business value chain involving a variety of partners to deliver products and services. Business to business (B2B) connectivity, Enterprise Application Integration (EAI) and general business collaboration processes are becoming more critical in operating and managing efficient enterprises. The required level of inter and intra enterprise integration is generally a large undertaking and involves substantial development and customization efforts. In this paper, we propose an adaptive integration activity management approach based on web services technologies to reduce code changes associated with business process integration in a distributed collaboration environment. Specifically, we present a concept of activity chain to capture non-deterministic process flows as well as deterministic process flows in a uniform manner. Then an Activity Ontology is introduced to capture the integration requirements that include adaptation behaviors, action properties, business rules, and access control policy references. The unique ontology representation and management of the integration activities provides a uniform way to integrate additional internal and external business applications to reduce the need for pre-defined and hard-wired integration methods and to minimize code changes to existing components in an existing business collaboration and integration (B2B/EAI) infrastructure. In addition, a Petri-Net modeling exercise of the proposed integration activity management is performed to help better understand the actual system and improve the system design beforehand.