Dynamic business process modeling and verification for inter-organizational collaboration

To achieve an on-demand and dynamic composition model of inter-organizational business processes, a new approach for business process modeling and verification is introduced by using the pi-calculus theory. A new business process model which is multi-role, multi-dimensional, integrated and dynamic is proposed relying on inter-organizational collaboration. Compatible with the traditional linear sequence model, the new model is an M x N multi-dimensional mesh, and provides horizontal and vertical formal descriptions for the collaboration business process model. Finally, the pi-calculus theory is utilized to verify the deadlocks, livelocks and synchronization of the example models. The result shows that the proposed approach is efficient and applicable in inter-organizational business process modeling.

Analysis of response time probability distribution of workflows

An evaluation approach for the response time probability distribution of workflows based on the fluid stochastic Petri net formalism is presented. Firstly, some problems about stochastic workflow net modeling are discussed. Then how to convert a stochastic workflow net model into a fluid stochastic Petri net model is described. The response time distribution can be obtained directly upon the transient state solution of the fluid stochastic Petri net model. In the proposed approach, there are not any restrictions on the structure of workflow models, and the processing times of workflow tasks can be modeled by using arbitrary probability distributions. Large workflow models can be efficiently tackled by recursively using a net reduction technique.

利用Workflows打印书标和分库典藏账

详细介绍了图书馆如何利用美国Sirsi公司的Workflows程序打印书标和分库典藏帐的步骤。每项步骤中都包括设置属性、生成报表、报表转化、调整格式、注意事项等,尤其针对工作需要给出了设置打印格式的方法,具有一定的现实意义。本文还对该打印工作提出了若干建议。

Context-aware Workflow Model for Supporting Composite Workflows

In recent years, several researchers have applied workflow technologies for service automation on ubiquitous compating environments. However, most context-aware workflows do not offer a method to compose several workflows in order to get mare large-scale or complicated workflow. They only provide a simple workflow model, not a composite workflow model. In this paper, the autorhs propose a context-aware workflow model to support composite workflows by expanding the patterns of the existing context-aware wrY：flows, which support the basic woddlow patterns. The suggested workflow model of. fers composite workflow patterns for a context-aware workflow, which consists of various flow patterns, such as simple, split, parallel flows, and subflow. With the suggested model, the model can easily reuse few of existing workflows to make a new workflow. As a result, it can save the development efforts and time of context-aware workflows and increase the workflow reusability. Therefore, the suggested model is expected to make it easy to develop applications related to context-aware workflow services on ubiquitous computing environments.

Adaptive resource allocation for workflow containerization on Kubernetes

In a cloud-native era,the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes.However,when encountering continuous workflow requests and unexpected resource request spikes,the engine is limited to the current workflow load information for resource allocation,which lacks the agility and predictability of resource allocation,resulting in over and underprovisioning resources.This mechanism seriously hinders workflow execution efficiency and leads to high resource waste.To overcome these drawbacks,we propose an adaptive resource allocation scheme named adaptive resource allocation scheme(ARAS)for the Kubernetes-based workflow engines.Considering potential future workflow task requests within the current task pod’s lifecycle,the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios.The ARAS offers resource discovery,resource evaluation,and allocation functionalities and serves as a key component for our tailored workflow engine(KubeAdaptor).By integrating the ARAS into KubeAdaptor for workflow containerized execution,we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS.Compared with the baseline algorithm,experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows,time-saving of 26.4% to 79.86% in the average duration of individual workflow,and an increase of 1% to 16% in centrol processing unit(CPU)and memory resource usage rate.

A novel group-based active service protocol for migrating workflows

Based on the methods of acquaintance cache and group-based intelligent forwarding of service recommendations,a novel group-based active service(GAS) protocol for migrating workflows was proposed.This protocol did not require service requesters to discover services or resources.The semantic acquaintance knowledge representation was exploited to describe service groups and this semantic information was used to recommend service to respective clients.The experimental results show that the new protocol proposed offers better performance than other protocols in terms of first-response-time,success-scope and ratio of success-packet-number to total-packet-number.When the number of service request packet is 20,the first-response-time of GAS protocol is only 5.1 s,which is significantly lower than that of other protocols.The success-scope of GAS protocol is 49.1%,showing that GAS protocol can effectively improve the reliability of mobile transactions.And the ratio of success-packet-number to total-packet-number of GAS protocol is up to 0.080,which is obviously higher than that of other protocols.

A New Methodology for Process Modeling of Workflows

Workflow-based systems are typically said to lead to better use of staff and better management and productivity. The first phase in building a workflow-based system is capturing the real-world process in a conceptual representation suitable for the following phases of formalization and implementation. The specification may be in text or diagram form or written in a formal language. This paper proposes a flow-based diagrammatic methodology as a tool for workflow specification. The expressiveness of the method is appraised though its ability to capture a workflow-based application. Here we show that the proposed conceptual diagrams are able to express situations arising in practice as an alternative to tools currently used in workflow systems. This is demonstrated by using the proposed methodology to partial build demo systems for two government agencies.

Effect of Management Maturity Levels on Inter-organizational Management in Value Chain Relations

This paper explains the current state of management control problems in inter-organizational relationships. There is a growing consensus that having cooperative relations with other organizations, building strategic supply chain relations, and establishing appropriate subsidiary-parent company relations are major components of a competitive strategy to increase organizational productivity and profitability. In this regard, we present samples collected from 60 Japanese companies, and provide a case study on the use of inter-organizational management control systems （MCSs） by a large Japanese manufacturing company. The findings show how a company can design its organizational structure in order to realize its strategies and achieve its goals. Further, the case study shows the importance of management control factors that are associated with activities in inter-organizational value chain relations. In particular, high management maturity in information management, cultural management, and structural management are identified as key factors for the integration of strategy with sustainable inter-organizational management.

A framework for interoperability of BPEL-based workflows

With the prevalence of service-oriented architecture （SOA）, web services have become the dominating technology to construct workflow systems. As a workflow is the composition of a series of interrelated web services which realize its activities, the interoperability of workflows can be treated as the composition of web services. To address it, a framework for interoperability of business process execution language （BPEL）-based workflows is presented, which can perform three phases, that is, transformation, eonformance test and execution. The core components of the framework are proposed, especially how these components promote interoperability. In particular, dynamic binding and re-composition of work-flows in terms of web service testing are presented. Besides, an example of business-to-business （B2B） collaboration is provided to illustrate how to perform composition and conformance test.

Efficient Computation Offloading of IoT-Based Workflows Using Discrete Teaching Learning-Based Optimization

As the Internet of Things(IoT)and mobile devices have rapidly proliferated,their computationally intensive applications have developed into complex,concurrent IoT-based workflows involving multiple interdependent tasks.By exploiting its low latency and high bandwidth,mobile edge computing(MEC)has emerged to achieve the high-performance computation offloading of these applications to satisfy the quality-of-service requirements of workflows and devices.In this study,we propose an offloading strategy for IoT-based workflows in a high-performance MEC environment.The proposed task-based offloading strategy consists of an optimization problem that includes task dependency,communication costs,workflow constraints,device energy consumption,and the heterogeneous characteristics of the edge environment.In addition,the optimal placement of workflow tasks is optimized using a discrete teaching learning-based optimization(DTLBO)metaheuristic.Extensive experimental evaluations demonstrate that the proposed offloading strategy is effective at minimizing the energy consumption of mobile devices and reducing the execution times of workflows compared to offloading strategies using different metaheuristics,including particle swarm optimization and ant colony optimization.

Inter-Organizational Conflict (IOC) in Building Refurbishment Projects;an Exploratory Factor Analysis (EFA) approach

Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.

FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.

基于工作流的无服务边缘计算框架设计与实现

边缘计算具有高性能、体积小、计算力超强等优点。但云设计的边缘计算函数链存在调用时延较长的问题,导致大规模部署和存储能力以及云端和设备端协同困难、无缝对接效果较差。为解决上述问题,基于开源无服务平台OpenFaaS设计了一个无服务边缘计算框架(SECP),为边缘侧提供基于无状态函数的计算服务。对计算服务调用过程采用建模分析,采用了工作流模型对为云设计的无服务计算在边缘侧存在的函数链式调用时延放大的问题改进。性能测试结果表明,SECP在边缘计算场景下有良好的性能表现,降低了边缘计算平台中服务请求的响应时间,解决了无服务计算函数功能单一问题,提高了边缘侧资源的利用率,并改善了边缘侧计算服务部署、维护繁杂的问题。

时间约束下的云工作流动态混合资源调度

随着云计算的出现和云基础设施的快速部署,越来越多的大型工作流应用正在积极向云迁移.同时,如何在满足任务时间约束的前提下优化执行成本,提高资源利用率成为新的挑战.本文提出一种云工作流动态混合资源调度算法DHRS,不仅满足任务的时间约束而且在混合资源租用时取得较低的成本.首先,根据任务的优先级关系对任务进行预处理,基于概率升序对任务进行排序,并为子任务分配子截止日期;然后,依据顺序为工作流选择满足截止日期且成本较低的服务;最后,对每个服务动态选择预留资源和按需资源,基于预留资源的空闲时间段调度,进一步降低成本.在随机生成的不同的科学工作流上进行实验,并通过与现有算法对比,DHRS在满足时间约束并且降低执行成本方面具有一定的优势.

面向工业互联网数据分析的机器学习工作流推荐方法

工业大数据具有多模态和强关联等特性,这给数据分析与应用带来了新的挑战。如何根据工业应用需求的特点实施有效的数据分析过程通常是一项非常复杂、耗时耗力的任务。针对该问题,提出一种面向工业互联网数据分析的机器学习工作流推荐方法。该方法以已有解决方案为起点,将其所使用的数据集和机器学习工作流作为推荐参考,基于Doc2vec模型与最大平均差异方法计算文本描述相似度与数据分布特征相似度,可根据当前数据分析任务需求,推荐合适的已有解决方案中的机器学习工作流。仿真实验说明了该方法的有效性。

执行时间预测驱动的工作流作业调度

针对工作流作业调度问题,提出使用关键路径法进行工作流的执行时间预测和资源分配。工作流执行时间预测算法使用并行应用有向无环图描述工作流中子作业的执行顺序。基于此顺序,为子作业进行系统资源的逻辑分配。根据子作业的特征和资源分配信息,使用梯度提升决策树进行子作业执行时间预测,并计算工作流的关键路径。关键路径上所有子作业的完成时间之和即为工作流的执行时间。若预测的工作流执行时间满足用户要求,则根据子作业执行顺序和资源分配方案进行作业调度,执行工作流。对比实验表明,两个工作流的执行时间预测误差分别为5.72%和1.57%。与Spark默认调度算法相比,工作流调度算法将两个工作流的完成时间分别缩短了15.71%和15.44%。

基于Kubernetes的工业AI项目开发平台

随着人工智能(AI)成为改变世界的前沿技术,企业也迫切需要系统地开发和实现人工智能来升级新一代工业系统的基础。考虑到将人工智能应用开发集成到工业开发中存在开发流程环节多、AI项目开发人员能力背景不一等问题,以企业实际需求为背景设计实现了一个AI项目开发平台。探讨了人工智能项目开发平台的概念和实现,并且基于企业实际需求对其进行定制化。在传统开发流程基础上完善更多开发工作流环节。在企业内部成功进行部署和测试。结果表明:项目开发平台的功能合理、运行正常、管理便捷对AI项目开发效率、体验、规范化有积极影响,提高了计算加速部件利用率。

高性能CAE软件性能评测平台的设计与应用

高性能计算机辅助工程(CAE)软件在复杂多物理过程仿真、大规模高逼真度数值模拟中发挥重要作用。高性能CAE软件的性能评测是衡量它性能指标的重要手段。传统手工基于算例评测的方式难以适应批量软件大量算例的并发评测,数据采集、性能分析等各阶段的数据管理、资源调度、性能指标计算以及评测报告撰写等活动脱节,制约高性能CAE软件的研发效率和评估效率。从高性能CAE软件研发模式和性能评测的需求出发,提出性能评测的数据模型和执行模型,基于科学工作流技术实现多软件、多算例、多规模的三层嵌套并发评测,设计并实现了高性能CAE软件性能评测平台,平台采用松耦合的可执行组件封装技术,提供软件和算例等信息管理、超算资源无缝对接、评测流程自动化执行和评测报告自动生成功能,在实际项目中采用该平台完成了数十个软件上百算例的并发评测。

高校图书馆手稿数字化与在线揭示的实践研究——以华东师范大学图书馆手稿数据库建设为例

国内高校图书馆收藏了大量的纸质手稿,但由于缺少数字化、长期保存以及在线揭示的整体解决方案,无法有效发挥其价值。本研究在手稿数据库需求分析的基础上,以华东师范大学手稿数据库建设为例,利用开源软件Goobi实现分布式手稿加工与发布,借助人工智能技术对手稿进行深度挖掘,基于IIIF的底层架构使特藏库可以整合国际知名文化遗产机构发布的手稿资源到本地。根据手稿资源的特点,构建手稿在线阅读图像工具、注释转录、手写识别、特征识别、自动标签等功能,提升用户体验。未来还将不断探索名人角色扮演参考咨询、多光谱三维手稿浏览以及手稿鉴定等功能,推动国内高校图书馆手稿数据库的建设。