Adaptive grid job scheduling with genetic algorithms

This paper proposes two models for predicting the completion time of jobs in a service Grid. The single service model predicts the completion time of a job in a Grid that provides only one type of service. The multiple services model predicts the completion time of a job that runs in a Grid which offers multiple types of services. We have developed two algorithms that use the predictive models to schedule jobs at both system level and application level. In application-level scheduling, genetic algorithms are used to minimize the average completion time of jobs through optimal job allocation on each node. The experimental results have shown that the scheduling system using the adaptive scheduling algorithms can allocate service jobs efficiently and effectively.