基于时间Petri网的工作流系统模型的线性推理

目前工作流理论的研究主要集中在工作流管理模型的结构及正确性分析,很少有人研究与时间有关的工作流模型的性质,特别是模型中的时序关系推理及性能计算问题.本文重点研究了这方面的问题,用时间Petri网表示工作流模型并对基本工作流模型进行时序分析,给出线性时间推理的规则,运用这些规则,可对复杂的工作流模型进行逐步化简,并在线性时间复杂度内解决时间推理问题.     

Dynamic Reconfiguration Based on Goal-Scenario by Adaptation Strategy

The self-adaptation of software systems is a complex process that depends on several factors that can change during the system operational lifetime. But, Today’s workflow management systems are only applicable in a secure and safe manner if the business process to be supported is well-structured and there is no need for ad hoc deviations at runtime. Hence, it is necessary to define mechanisms for providing a self-adaptive system the capability of reconfiguration during run-time the process that controls its adaptation. In this paper, we provide rapid dynamic reconfiguration using the workflow based on goal-scenario as the basis to set up strategies in accordance with the adaptive judgment. Also, we provide a sophisticated approach which fosters learning from past process changes by process variants through the order matrix. We present a formal foundation for the support of dynamic structural workflow changes of running. Our approach uses estimates based goal-scenario to determine which remaining parts of running workflows are affected by the external environment and is able to predictively perform suitable adaptation. This helps to ensure that necessary adaptation are performed in time with minimal user interaction which is especially valuable in change of external environment.     

基于生成图的工作流多过程动态 时序一致性验证方法

 提出了基于生成图的多过程动态时序一致性验证方法.首先从多过程的时间工作流网构建生成图,以图形化方式表达实例可能经过的路径和时间信息.在动态检测时,依据已经完成活动对生成图进行部分更新,再利用图中节点相关信息进行时间约束的验证.该方法可以解决资源约束情况下多过程时序一致性动态验证问题,而且能定位模型中出问题的路径,指导用户进行工作流时序异常处理或优化工作流模型;另一方面,生成图可供多个时序约束进行验证使用,具有较好的可重用性.     

An agent‐based workflow scheduling mechanism with deadline constraint on hybrid cloud environment

Summary

With the advances of cloud computing, business and scientific‐oriented jobs with certain workflows are increasingly migrated to and run on a variety of cloud environments. These jobs are often with the property of deadline constraint and have to be completed within limited time. Therefore, to schedule a job with workflow (short for workflow) with deadline constraint is increasingly becoming a crucial research issue. In this paper, we, based on previous work, propose an agent‐based workflow scheduling mechanism to schedule workflows that are with deadline constraint into federated cloud environment.

Design and Methods

We add a workflow agent into the original framework to schedule the deadline‐constraint workflow. The workflow agent can smoothly schedule workflows to the cloud system according to their required resource and automatically monitor their execution. In order to accurately predict the execution time of each task to meet deadline constraint on certain VM with given resource, we inherit the use of rough set theory to estimate execution time of task in our previous work.

Result and Discussion

A heuristic algorithm that is embedded into the workflow agent is also proposed because the problem had been shown to be NP‐complete. The mechanism also adopts dynamic job dispatching method to reduce the usage of VM and to improve the resource utilization. We also conducted experiments to evaluate the efficiency and effectiveness.

Conclusion

The experimental results show that the prediction time is very close to the real execution time and can efficiently schedule multiple scientific workflows to meet the deadline constraints simultaneously.     

Multiscale Bayesian segmentation using a trainable context model

Multiscale Bayesian approaches have attracted increasing attention for use in image segmentation. Generally, these methods tend to offer improved segmentation accuracy with reduced computational burden. Existing Bayesian segmentation methods use simple models of context designed to encourage large uniformly classified regions. Consequently, these context models have a limited ability to capture the complex contextual dependencies that are important in applications such as document segmentation. We propose a multiscale Bayesian segmentation algorithm which can effectively model complex aspects of both local and global contextual behavior. The model uses a Markov chain in scale to model the class labels that form the segmentation, but augments this Markov chain structure by incorporating tree based classifiers to model the transition probabilities between adjacent scales. The tree based classifier models complex transition rules with only a moderate number of parameters. One advantage to our segmentation algorithm is that it can be trained for specific segmentation applications by simply providing examples of images with their corresponding accurate segmentations. This makes the method flexible by allowing both the context and the image models to be adapted without modification of the basic algorithm. We illustrate the value of our approach with examples from document segmentation in which test, picture and background classes must be separated.     

An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements

Grid computing is increasingly considered as a promising next-generation computational platform that supports wide-area parallel and distributed computing. In grid environments, applications are always regarded as workflows. The problem of scheduling workflows in terms of certain quality of service (QoS) requirements is challenging and it significantly influences the performance of grids. By now, there have been some algorithms for grid workflow scheduling, but most of them can only tackle the problems with a single QoS parameter or with small-scale workflows. In this frame, this paper aims at proposing an ant colony optimization (ACO) algorithm to schedule large-scale workflows with various QoS parameters. This algorithm enables users to specify their QoS preferences as well as define the minimum QoS thresholds for a certain application. The objective of this algorithm is to find a solution that meets all QoS constraints and optimizes the user-preferred QoS parameter. Based on the characteristics of workflow scheduling, we design seven new heuristics for the ACO approach and propose an adaptive scheme that allows artificial ants to select heuristics based on pheromone values. Experiments are done in ten workflow applications with at most 120 tasks, and the results demonstrate the effectiveness of the proposed algorithm.     

Hamming distance preserving mappings and trellis codes withconstrained binary symbols

The transformation of a linear convolutional code into a run-length-constrained or balanced trellis code with the same or larger free distance is investigated. The transformation involves a Hamming-distance-preserving mapping of the set of unconstrained binary symbols of the convolutional code onto a set of suitably constrained symbols. Simple tests to determine if these mappings can exist and a tree search algorithm for finding such mappings are presented     

基于SharePoint企业工作流管理系统设计

工作流管理系统能够提高企业的生产效率,可以有效地加快企业的信息化建设的步伐。阐述了工作流管理系统的应用背景和系统结构,提出了基于微软公司的SharePoint信息化应用平台的企业工作流管理系统设计方案,提供了可视化的工作流模板定义方式,使用户可以直观、方便地自定义工作流模板,并扩展出其他现有系统的接口,从而实现工作流管理系统的灵活性和可扩展性。     

一种层次式的事务工作流失效恢复算法

部分补偿和完全补偿是事务工作流失效恢复的传统补偿方法,对于长期运行且结构复杂的事务工作流,失效时需要补偿至静态定义的某一活动甚至起始活动,因此代价较大.给出了事务工作流的概念模型,提出了一种层次式的失效恢复算法.与传统方法相比,允许事务性或者非事务性子过程同时存在;将工作流看作由嵌套结构的子过程组成,而不是一个平坦流图;基于执行历史而不是工作流定义进行补偿,可简化循环结构的恢复.该算法针对活动的恢复策略进行层次式的向上规约处理,动态确定补偿终止点,可有效减小补偿域.证明了算法的正确性,性能分析表明其性能通常优于非层次的失效恢复算法,讨论了算法的实现.     

Adaptive-logic trees for use in multilevel-circuit design

A logic tree employing only 2-input gates is described which is capable of mechanising any desired function of the variable set. The tree can therefore represent either a fixed relationship, or vary adaptively by adjusting the input parameters. It is shown that this structure can be used to derive economic multilevel representations of functions directly from the canonical form which require only 2-input gates. The design procedure can operate effectively with only a simple set of design rules.     

工作流管理系统及其管理接口技术研究

随着计算机和网络技术的普及,工作流技术得到了迅速发展和广泛应用。对工作流管理系统的核心概念进行了阐述,重点分析了工作流主要组成、基本模型以及管理接口的技术特性和主要概念。结合XML技术良好的灵活性、拓展性以及跨平台能力,建立了基于XML技术的工作流管理接口模型结构,提出了工作流管理接口的一种实现技术,能较好地满足工作流系统在分布式处理的灵活、扩展要求。     

Inheritance Optimization of Extend Case Transfer Model of Interoganization Workflows Management

1IntroductionToday,many corporations are extending their mar-kets by mergers and strategic alliances with other com-panies throughout the world.The Collaboration Com-merce(C-commerce)is presented,which the businessprocesses are key facture to i mplementin…     

一种基于QoS的事务工作流并发调度算法

并发冲突引起的连锁夭折会降低系统性能,提出了一种基于QoS的事务工作流调度算法,该算法适应异构环境需求,支持基于QoS的延迟调度优化策略和SAFE集合扩充优化策略,可根据QoS参数调整相应的调度决策,在保证分布异构环境中复杂事务工作流并发正确性的同时减少连锁夭折.证明了算法不会引起循环等待和饿死现象,可保证调度的可串行性和可恢复性,性能模拟表明该算法适用于长期运行的事务工作流的并发调度,可有效减少连锁夭折,从而减少由此带来的性能损失.     

一种基于RFID数据集的物品工作流挖掘方法

 不同种类的物品在供应链中的移动形成不同的物品工作流,通过对这些物品工作流的挖掘,能够发现不同种类物品的流向和主要流转路径等信息,进而基于这些信息对供应链过程进行管理和优化.本文提出了一种基于RFID数据集的物品工作流挖掘方法,其中定义了一种基于Petri网的物品工作流网,讨论了物品工作流网所支持的几种物品工作流模式,给出了基于RFID数据集的数据过滤和聚合算法,以及物品工作流网的挖掘算法,最后进行了必要的实验.     

工作流技术在电信运营系统业务流程重组中的应用研究

工作流技术的研究和实现已经成为计算机应用领域的一个热点，其构建的信息系统具有很好的灵活性和良好的可扩展能力。本文介绍了工作流技术，并以电信运营系统业务流程重组(BPR)为背景，分析了工作流技术的具体实现，主要包括工作流定义、BPR理念、工作流模型、实施步骤几个方面。     

Agent在工作流管理系统中的应用研究

当前,大多数工作流管理系统都是独立地管理单个工作流,而忽视了工作流之间的资源约束关系,基于ａｇｅｎｔ 的工作流管理系统能够有效地解决这个问题。本文主要讨论基于 ａｇｅｎｔ 的工作流管理系统包括系统配置、工作流执行的动态调度以及多 ａｇｅｎｔ 系统的组织和通信问题。     

Automated Diagnosis of Coronary Artery Disease Based on Data Mining and Fuzzy Modeling

A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.     

Autonomic workflow execution in the grid

Mobile agents are being leveraged in both workflow management and grid computing contexts. The convergence of these two research streams supports execution in the grid where tasks are allowed to vary in their level of interdependence. The result is an expansion of grid applications beyond those which consist of homogeneous computations decomposed and performed in parallel to those which support the parallel execution of sequences of interdependent tasks that constitute a workflow. However, grid computation of critical workflows requires that the grid platform exhibits the autonomic characteristic of self-healing in order to ensure workflow execution. To address this issue, in this work, we first develop a model for dynamic fault tolerance technique selection, which can be embedded generically in a mobile agent workflow management system. We then augment an existing architecture for flexible fault tolerance in the grid with our model, thus allowing the system to optimally configure its fault tolerance mechanisms through awareness of the computational environment. The result is a foundation for autonomic workflow management in the grid.     

A framework for enhancing mobile workflow execution through injection of flexible security controls

Mobile workflow execution is gaining importance as traditional process execution systems are employed in many new scenarios such as mobile networks or the Internet of Things. Unfortunately, in these solutions, security is still based on control loops or computer science techniques which have not evolved as fast as current mobile systems and applications. In this context, in order to improve the security level of these systems, it is necessary to create a security framework tightly coupled with the mobile workflow execution platforms. To contribute filling this gap, we propose a framework to inject security controls in workflows, which supports mobile execution and allows a flexible decision making. This solution models security as control points where some relevant previously defined indicators are evaluated. Depending on the obtained values, the framework takes corrective, preventive or adaptive actions, considering also the execution system capabilities and the workflow being executed. In order to evaluate the effectiveness and performance of the proposed solution we include experimental validation.