A budget constrained scheduling of workflow applications on utility grids using genetic algorithms

Abstract

Over the last few years, Grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on their QoS (Quality of Service) requirements. In such "pay-per-use" Grids, workflow execution cost must be considered during scheduling based on users' QoS constraints. In this paper, we propose a budget constraint based scheduling, which minimizes execution time while meeting a specified budget for delivering results. A new type of genetic algorithm is developed to solve the scheduling optimization problem and we test the scheduling algorithm in a simulated Grid testbed.