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 Taxonomy of Workflow Management Systems for Grid Computing

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. 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.

https://www.cct.lsu.edu/~kosar/csc7700-fall06/papers/Yu05.pdf

A taxonomy of scientific workflow systems for grid computing

To program in distributed computing environments such as grids and clouds, workflow is adopted as an attractive paradigm for its powerful ability in expressing a wide range of applications, including scientific computing, multi-tier Web, and big data processing applications. With the development of cloud technology and extensive deployment of cloud platform, the problem of workflow scheduling in cloud becomes an important research topic. The challenges of the problem lie in: NP-hard nature of task-resource mapping; diverse QoS requirements; on-demand resource provisioning; performance fluctuation and failure handling; hybrid resource scheduling; data storage and transmission optimization. Consequently, a number of studies, focusing on different aspects, emerged in the literature. In this paper, we firstly conduct taxonomy and comparative review on workflow scheduling algorithms. Then, we make a comprehensive survey of workflow scheduling in cloud environment in a problem---solution manner. Based on the analysis, we also highlight some research directions for future investigation.

Workflow scheduling in cloud: a survey

Scientific workflow design for mere mortals

The generic, heterogeneous, and dynamic nature of the grid requires a new from of failure recovery mechanism to address its unique requirements such as support for diverse failure handling strategies, separation of failure handling strategies from application codes, and user-defined exception handling. We here propose a grid workflow system (grid-WFS), a flexible failure handling framework for the grid, which addresses these grid-unique failure recovery requirements. Central to the framework is flexibility by the use of workflow structure as a high-level recovery policy specification. We show how this use of high-level workflow structure allows users to achieve failure recovery in a variety of ways depending on the requirements and constraints of their applications. We also demonstrate that this use of workflow structure enables users to not only rapidly prototype and investigate failure handling strategies, but also easily change them by simply modifying the encompassing workflow structure, while the application code remains intact. Finally, we present an experimental evaluation of our framework using a simulation, demonstrating the value of supporting multiple failure recovery techniques in grid systems to achieve high performance in the presence of failures.

Soonwook Hwang

Papers

Grid workflow: a flexible failure handling framework for the grid