An Architectural Model for a Grid based Workflow Management Platform in Scientific Applications

TL;DR

This paper proposes an architectural model for a grid-based workflow management platform tailored for scientific applications, emphasizing usability, data handling, and fault tolerance to improve automation in complex distributed computing environments.

Contribution

It introduces a novel architectural framework with an extended workflow engine and scheduling component to enhance usability and efficiency for scientific workflow automation.

Findings

Enhanced workflow description interface for scientists

Efficient data handling mechanisms implemented

Flexible fault tolerance support integrated

Abstract

With recent increasing computational and data requirements of scientific applications, the use of large clustered systems as well as distributed resources is inevitable. Although executing large applications in these environments brings increased performance, the automation of the process becomes more and more challenging. While the use of complex workflow management systems has been a viable solution for this automation process in business oriented environments, the open source engines available for scientific applications lack some functionalities or are too difficult to use for non-specialists. In this work we propose an architectural model for a grid based workflow management platform providing features like an intuitive way to describe workflows, efficient data handling mechanisms and flexible fault tolerance support. Our integrated solution introduces a workflow engine component based on ActiveBPEL extended with additional functionalities and a scheduling component providing efficient mapping between tasks and available resources.