基于行为和结构特征的相似语义工作流检索

相似语义工作流检索是语义工作流重用的首要任务.现有的相似语义工作流检索方法仅关注结构特征,忽略了行为特征,影响了检索到的相似语义工作流的整体质量,提高了语义工作流重用的代价.为此,提出一种结合行为和结构特征的2阶段相似语义工作流检索算法.使用任务紧邻关系集表达语义工作流的执行行为,结合领域知识构造语义工作流库的任务紧邻关系树索引和数据索引.针对查询语义工作流,先基于任务紧邻关系树索引和数据索引进行过滤得到候选语义工作流集;然后使用图匹配相似性算法对候选语义工作流集进行验证,得到排序的候选语义工作流集.实验结果表明,较主流的语义工作流检索算法,该方法的检索性能有较大提升,可以为工作流重用提供更高质量的语义工作流.     

Abstract,link, publish,exploit: An end to end framework for workflow sharing

Scientific workflows are increasingly used to manage and share scientific computations and methods to analyze data. A variety of systems have been developed that store the workflows executed and make them part of public repositories However, workflows are published in the idiosyncratic format of the workflow system used for the creation and execution of the workflows. Browsing, linking and using the stored workflows and their results often becomes a challenge for scientists who may only be familiar with one system. In this paper we present an approach for addressing this issue by publishing and exploiting workflows as data on the Web with a representation that is independent from the workflow system used to create them. In order to achieve our goal, we follow the Linked Data Principles to publish workflow inputs, intermediate results, outputs and codes; and we reuse and extend well established standards like W3C PROV. We illustrate our approach by publishing workflows and consuming them with different tools designed to address common scenarios for workflow exploitation.     

工作流技术在新一代电信运营综合管理支撑系统中的应用研究

介绍了工作流技术并以电信运营综合管理系统 (Business &Operation Support System,简称 BOSS)为背景 ,分析了工作流技术的具体实现 ,主要包括工作流技术介绍 ,工作流支撑的 BOSS架构、BOSS参考模型、BOSS体系结构、BOSS数据中心模型等几个方面     

Common motifs in scientific workflows: An empirical analysis

Workflow technology continues to play an important role as a means for specifying and enacting computational experiments in modern science. Reusing and re-purposing workflows allow scientists to do new experiments faster, since the workflows capture useful expertise from others. As workflow libraries grow, scientists face the challenge of finding workflows appropriate for their task, understanding what each workflow does, and reusing relevant portions of a given workflow. We believe that workflows would be easier to understand and reuse if high-level views (abstractions) of their activities were available in workflow libraries. As a first step towards obtaining these abstractions, we report in this paper on the results of a manual analysis performed over a set of real-world scientific workflows from Taverna, Wings, Galaxy and Vistrails. Our analysis has resulted in a set of scientific workflow motifs that outline (i) the kinds of data-intensive activities that are observed in workflows (Data-Operation motifs), and (ii) the different manners in which activities are implemented within workflows (Workflow-Oriented motifs). These motifs are helpful to identify the functionality of the steps in a given workflow, to develop best practices for workflow design, and to develop approaches for automated generation of workflow abstractions.     

Visualization workflows for level-12 HUC scales: Towards an expert system for watershed analysis in a distributed computing environment

Visualization workflows are important services for expert users to analyze watersheds when using our HydroTerre end-to-end workflows. Analysis is an interactive and iterative process and we demonstrate that the expert user can focus on model results, not data preparation, by using a web application to rapidly create, tune, and calibrate hydrological models anywhere in the continental USA (CONUS). The HydroTerre system captures user interaction for provenance and reproducibility to share modeling strategies with modelers. Our end-to-end workflow consists of four workflows. The first is data workflows using Essential Terrestrial Variables (ETV) data sets that we demonstrated to construct watershed models anywhere in the CONUS (Leonard and Duffy, 2013). The second is data-model workflows that transform the data workflow results to model inputs. The model inputs are consumed in the third workflow, model workflows (Leonard and Duffy, 2014a) that handle distribution of data and model within High Performance Computing (HPC) environments. This article focuses on our fourth workflow, visualization workflows, which consume the first three workflows to form an end-to-end system to create and share hydrological model results efficiently for analysis and peer review. We show how visualization workflows are incorporated into the HydroTerre infrastructure design and demonstrate the efficiency and robustness for an expert modeler to produce, analyze, and share new hydrological models using CONUS national datasets.     

基于行为特征的语义工作流修正算法

工作流修正是工作流重用的重要任务.目前在基于工作流的可重用片段——stream的语义工作流修正中,当工作流stream库中不存在与检索语义工作流中的工作流stream结构相似的stream时,无法修正检索工作流.针对这种情况,提出了一种改进方案——基于stream行为特征修正语义工作流.使用任务紧邻关系集表达stream的行为特征.对于检索语义工作流中的每个与变更请求不一致的stream,使用锚集合数据索引和stream匹配规则对工作流stream库过滤得到候选匹配stream集;之后基于stream的行为相似性和变更请求对候选stream集进行验证,得到与变更请求一致程度最高和足够相似的匹配stream;然后更新变更请求,使用每个检索到的匹配stream替换原stream以逐步修正检索语义工作流中的缺陷;最后得到修正语义工作流.实验结果表明,与现有的基于工作流stream的修正算法相比,本文的算法得到了整体质量更好的修正语义工作流集,其适应性更好.该修正算法能为业务过程管理人员为适应新业务需求的工作流建模提供较好质量的修正语义工作流供参考,对提高工作流重用的效率和质量有较大帮助.     

SEAM: A state-entity-activity-model for a well-defined workflowdevelopment methodology

Current conceptual workflow models use either informally defined conceptual models or several formally defined conceptual models that capture different aspects of the workflow, e.g., the data, process, and organizational aspects of the workflow. To the best of our knowledge, there are no algorithms that can amalgamate these models to yield a single view of reality. A fragmented conceptual view is useful for systems analysis and documentation. However, it fails to realize the potential of conceptual models to provide a convenient interface to automate the design and management of workflows. First, as a step toward accomplishing this objective, we propose SEAM (State-Entity-Activity-Model), a conceptual workflow model defined in terms of set theory. Second, no attempt has been made, to the best of our knowledge, to incorporate time into a conceptual workflow model. SEAM incorporates the temporal aspect of workflows. Third, we apply SEAM to a real-life organizational unit's workflows. In this work, we show a subset of the workflows modeled for this organization using SEAM. We also demonstrate, via a prototype application, how the SEAM schema can be implemented on a relational database management system. We present the lessons we learned about the advantages obtained for the organization and, for developers who choose to use SEAM, we also present potential pitfalls in using the SEAM methodology to build workflow systems on relational platforms. The information contained in this work is sufficient enough to allow application developers to utilize SEAM as a methodology to analyze, design, and construct workflow applications on current relational database management systems. The definition of SEAM as a context-free grammar, definition of its semantics, and its mapping to relational platforms should be sufficient also, to allow the construction of an automated workflow design and construction tool with SEAM as the user interface     

Effective and efficient similarity search in scientific workflow repositories

Scientific workflows have become a valuable tool for large-scale data processing and analysis. This has led to the creation of specialized online repositories to facilitate workflow sharing and reuse. Over time, these repositories have grown to sizes that call for advanced methods to support workflow discovery, in particular for similarity search. Effective similarity search requires both high quality algorithms for the comparison of scientific workflows and efficient strategies for indexing, searching, and ranking of search results. Yet, the graph structure of scientific workflows poses severe challenges to each of these steps. Here, we present a complete system for effective and efficient similarity search in scientific workflow repositories, based on the Layer Decomposition approach to scientific workflow comparison. Layer Decomposition specifically accounts for the directed dataflow underlying scientific workflows and, compared to other state-of-the-art methods, delivers best results for similarity search at comparably low runtimes. Stacking Layer Decomposition with even faster, structure-agnostic approaches allows us to use proven, off-the-shelf tools for workflow indexing to further reduce runtimes and scale similarity search to sizes of current repositories.     

Social workflows—Vision and potential study

Social workflows pervade peoples׳ everyday life. Whenever a group of persons works together on a challenging or multifaceted task, a social workflow begins. Unlike traditional business workflows, such social workflows aim at supporting processes that contain personal tasks and data. In this work, we envision a social workflow service as part of a social network that enables private individuals to construct social workflows according to their specific needs and to keep track of the workflow execution. The proposed features for a social workflow service could help individuals to accomplish their private goals. The presented idea is contrasted with established research areas and applications to show the degree of novelty of this work. It is shown how novel ideas for knowledge management, facilitated by a process-oriented case-based reasoning approach, support private individuals and how they can obtain an appropriate social workflow through sharing and reuse of respective experience. Two empirical studies confirm the potential benefits of a social workflow service in general and the core features of the developed concept.     

Workflow View Based E-Contracts in a Cross-Organizational E-Services Environment

In an e-service environment, workflow involves not only a single organization but also a number of business partners. Therefore, workflow inter-operability in such an environment is an important issue for enacting workflows. In this article, we introduce our approach of using workflow views as a fundamental support for E-service workflow inter-operability and for controlled visibility of (sub-)workflows by external parties. We discuss various aspects of a workflow view, and their semantics with example usage. Furthermore, we develop a contract model based on workflow views and demonstrate how management of e-contracts can be facilitated, with an Internet start-up E-service inter-organization workflow example.     

Scientific workflows in data analysis: Bridging expertise across multiple domains

In this paper, we demonstrate the use of scientific workflows in bridging expertise across multiple domains by re-purposing workflow fragments in the areas of text analysis, image analysis, and analysis of activity in video. We highlight how the reuse of workflows allows scientists to link across disciplines and avail themselves of the benefits of inter-disciplinary research beyond their normal area of expertise. In addition, we present in-depth studies of various tasks, including tasks for text analysis, multimedia analysis involving both images and text, video activity analysis, and analysis of artistic style using deep learning. These tasks show how the re-use of workflow fragments can turn a pre-existing, rudimentary approach into an expert-grade analysis. We also examine how workflow fragments save time and effort while amalgamating expertise in multiple areas such as machine learning and computer vision.     

Similarity assessment and efficient retrieval of semantic workflows

In the recent years, the use of workflows has significantly expanded from its original domain of business processes towards new areas. The increasing demand for individual and more flexible workflows asks for new methods that support domain experts to create, monitor, and adapt workflows. The emergent field of process-oriented case-based reasoning addresses this problem by proposing methods for reasoning with workflows based on experience. New workflows can be constructed by reuse of already available similar workflows from a repository. Hence, methods for the similarity assessment of workflows and for the efficient retrieval of similar workflows from a repository are of core importance. To this end, we describe a new generic model for representing workflows as semantically labeled graphs, together with a related model for knowledge intensive similarity measures. Further, new algorithms for workflow similarity computation, based on A⁎ search are described. A new retrieval algorithm is introduced that goes beyond traditional sequential retrieval for graphs, interweaving similarity computation with case selection. We describe the application of this model and several experimental evaluations of the algorithms in the domain of scientific workflows and in the domain of business workflows, thereby showing its broad applicability.     

A Provenance-based Adaptive Scheduling Heuristic for Parallel Scientific Workflows in Clouds

In the last years, scientific workflows have emerged as a fundamental abstraction for structuring and executing scientific experiments in computational environments. Scientific workflows are becoming increasingly complex and more demanding in terms of computational resources, thus requiring the usage of parallel techniques and high performance computing (HPC) environments. Meanwhile, clouds have emerged as a new paradigm where resources are virtualized and provided on demand. By using clouds, scientists have expanded beyond single parallel computers to hundreds or even thousands of virtual machines. Although the initial focus of clouds was to provide high throughput computing, clouds are already being used to provide an HPC environment where elastic resources can be instantiated on demand during the course of a scientific workflow. However, this model also raises many open, yet important, challenges such as scheduling workflow activities. Scheduling parallel scientific workflows in the cloud is a very complex task since we have to take into account many different criteria and to explore the elasticity characteristic for optimizing workflow execution. In this paper, we introduce an adaptive scheduling heuristic for parallel execution of scientific workflows in the cloud that is based on three criteria: total execution time (makespan), reliability and financial cost. Besides scheduling workflow activities based on a 3-objective cost model, this approach also scales resources up and down according to the restrictions imposed by scientists before workflow execution. This tuning is based on provenance data captured and queried at runtime. We conducted a thorough validation of our approach using a real bioinformatics workflow. The experiments were performed in SciCumulus, a cloud workflow engine for managing scientific workflow execution.     

From Contracts to E-Contracts: Modeling and Enactment

Contracts are complex to understand, represent and process electronically. Usually, contracts involve various entities such as parties, activities and clauses. An e-contract is a contract modeled, specified, executed and enacted (controlled and monitored) by a software system (such as a workflow system). Workflows are used to automate business processes that govern adherence to the e-contracts. E-contracts can be mapped to inter-related workflows, which have to be specified carefully to satisfy the contract requirements. Most workflow models do not have the capabilities to handle complex inter/intra relationships among entities in e-contracts. An e-contract does not adhere to activity/task oriented workflow processes, thus generating a gap between a conceptual model of e-contract and workflow. In this paper, we describe conceptual modeling of e-contracts and present a business process model for e-contract enactment. The enactment of e-contracts necessitates dynamic generation and initiation of workflows during the e-contract execution, besides the static workflows. ER^EC business process model facilitates an integrated approach to e-contracts enactment. Our methodology is illustrated by means of a case study conducted using Financial Messaging Solution contract for banking transactions.     

基于领域本体的制造网格服务自动组合技术研究

为实现制造网格应用的自动化,提出了一个基于领域本体（ontology）的服务自动组合体系结构及其相应的算法。领域本体基于TOVE、STEP、PSL三个成熟的制造本体和网格服务概念模型构建。体系结构以语义结构良好的用户目标作为输入,输出预约的可执行工作流;通过基于领域本体推理的反向递归组合算法,能够实现本地仓库中工作流的重用和网格范围内服务的新工作流组合;支持抽象、具体两个层面的松耦合工作流组合（对应于编排（Choreography）和编制（Orchestration））;支持面向服务质量的工作流优化选择和工作流预约。实现了一个原型系统,实例的实验结果证明了该体系结构和算法的有效性。     

一个基于TWF-net的扩展时间工作流模型及其应用

时间约束是分布式企业工作流程建模中的一个重要因素．基于时间Petri网工作流模型(TWF-net)，通过分析TWF-net模型不足之处，建立了一种新的时间Petri网工作流模型——扩展时间Petri网工作流模型(XTWF-net)．通过构建规则，可将多个TWF-net合并为一个XTWF-net，以描述并行流程中的时间约束；通过引入与时区相关的时间映射函数，XTWF-net可以描述分布于不同时区的流程．最后给出一个利用XTWF-net描述分布式企业中业务流程的实例．     

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

Many scientific workflows are data intensive: large volumes of intermediate datasets are generated during their execution. Some valuable intermediate datasets need to be stored for sharing or reuse. Traditionally, they are selectively stored according to the system storage capacity, determined manually. As doing science on clouds has become popular nowadays, more intermediate datasets in scientific cloud workflows can be stored by different storage strategies based on a pay-as-you-go model. In this paper, we build an intermediate data dependency graph (IDG) from the data provenances in scientific workflows. With the IDG, deleted intermediate datasets can be regenerated, and as such we develop a novel algorithm that can find a minimum cost storage strategy for the intermediate datasets in scientific cloud workflow systems. The strategy achieves the best trade-off of computation cost and storage cost by automatically storing the most appropriate intermediate datasets in the cloud storage. This strategy can be utilised on demand as a minimum cost benchmark for all other intermediate dataset storage strategies in the cloud. We utilise Amazon clouds’ cost model and apply the algorithm to general random as well as specific astrophysics pulsar searching scientific workflows for evaluation. The results show that benchmarking effectively demonstrates the cost effectiveness over other representative storage strategies.     

On verification of nested workflows with extra constraints: From theory to practice

Workflows are used to formally describe processes of various types such as business and manufacturing processes. One of the critical tasks of workflow management is automated discovery of possible flaws in the workflow – workflow verification. In this paper, we formalize the problem of workflow verification as the problem of verifying that there exists a feasible process for each task in the workflow. This problem is tractable for nested workflows that are the workflows with a hierarchical structure similar to hierarchical task networks in planning. However, we show that if extra synchronization, precedence, or causal constraints are added to the nested structure, the workflow verification problem becomes NP-complete. We present a workflow verification algorithm for nested workflows with extra constraints that is based on constraint satisfaction techniques and exploits an incremental temporal reasoning algorithm. We then experimentally demonstrate efficiency of the proposed techniques on randomly generated workflows with various structures and sizes. The paper is concluded by notes on exploiting the presented techniques in the application FlowOpt for modeling, optimizing, visualizing, and analyzing production workflows.