Scheduling scientific workflow applications with deadline and budget constraints using genetic algorithms

Issue title: Scientific Workflows

Article type: Research Article

Authors: Yu, Jia | Buyya, Rajkumar

Affiliations: Grid Computing and Distributed Systems (GRIDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3010 Australia. E-mail: {jiayu,raj}@csse.unimelb.edu.au

Note: [] Corresponding author

Abstract: Grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distributed world wide to enhance the capability and performance. Many scientific applications in areas such as bioinformatics and astronomy require workflow processing in which tasks are executed based on their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments need to consider users' QoS requirements. In this paper, we present a genetic algorithm approach to address scheduling optimization problems in workflow applications, based on two QoS constraints, deadline and budget.

Keywords: Grid workflow, workflow scheduling, utility Grids, deadline constrained scheduling, budget constrained scheduling

Journal: Scientific Programming, vol. 14, no. 3-4, pp. 217-230, 2006