文件名称:Scheduling_Scientific_Workflow_Applications_with_
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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
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
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Scheduling_Scientific_Workflow_Applications_with_Deadline_and_Budget_Constraints_using.pdf