Workflow

About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.

A Taxonomy of Workflow Management Systems for Grid Computing

Abstract: With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.

A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments

Abstract: Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. However, users are charged on a pay-per-use basis. User applications may incur large data retrieval and execution costs when they are scheduled taking into account only the ‘execution time’. In addition to optimizing execution time, the cost arising from data transfers between resources as well as execution costs must also be taken into account. In this paper, we present a particle swarm optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost. We experiment with a workflow application by varying its computation and communication costs. We compare the cost savings when using PSO and existing ‘Best Resource Selection’ (BRS) algorithm. Our results show that PSO can achieve: a) as much as 3 times cost savings as compared to BRS, and b) good distribution of workload onto resources.

The future of crowd work

Abstract: Paid crowd work offers remarkable opportunities for improving productivity, social mobility, and the global economy by engaging a geographically distributed workforce to complete complex tasks on demand and at scale. But it is also possible that crowd work will fail to achieve its potential, focusing on assembly-line piecework. Can we foresee a future crowd workplace in which we would want our children to participate? This paper frames the major challenges that stand in the way of this goal. Drawing on theory from organizational behavior and distributed computing, as well as direct feedback from workers, we outline a framework that will enable crowd work that is complex, collaborative, and sustainable. The framework lays out research challenges in twelve major areas: workflow, task assignment, hierarchy, real-time response, synchronous collaboration, quality control, crowds guiding AIs, AIs guiding crowds, platforms, job design, reputation, and motivation.

Enterprise Application Integration

Abstract: Organizations that are able to integrate their applications and data sources have a distinct competitive advantage: strategic utilization of company data and technology for greater efficiency and profit. But IT managers attempting integration face daunting challenges--disparate legacy systems; a hodgepodge of hardware, operating systems, and networking technology; proprietary packaged applications; and more.Enterprise Application Integration (EAI) offers a solution to this increasingly urgent business need. It encompasses technologies that enable business processes and data to speak to one another across applications, integrating many individual systems into a seamless whole.Enterprise Application Integrationprovides a comprehensive examination of EAI. You will find an overview of EAI goals and approaches, a review of the technologies that support it, and a roadmap to implementing an EAI solution. You will also find an in-depth explanation of the four major types of EAI: data-level, application interface-level, method-level, and user interface-level. The book describes in detail the middleware models and technologies that support these different approaches, including: Application servers, including the use of Enterprise JavaBeans (EJB) and ActiveX Message-oriented middleware (MOM) and remote procedure calls (RPCs) Distributed objects, looking at CORBA and COM Database-oriented middleware and standards, including ODBC, JDBC, and OLE DB Java middleware standards Message brokers New process automation and workflow technologyThis practical guide to implementing an EAI solution leads you through all the major steps, including identifying sources of data, building the enterprise metadata model, process integration, identifying application interfaces, mapping information movement, selecting and applying the technologies, testing, and maintenance. Other key topics include integrating packaged applications such as SAP R/3 and PeopleSoft, integrating the supply chain using EAI, the role of XML, and process automation. Comprehensive, practical, and clearly written, this essential resource will help anyone involved in this important business area understand the nature of EAI, its tools and techniques, and how to apply it for a significant business advantage. 0201615835B04062001