Energy-Efficient Scientific Workflow Scheduling Algorithm in Cloud Environment

Scheduling extensive scientific applications that are deadline-aware (usually referred to as workflow) is a difficult task. This research provides virtual machine (VM) placement and scheduling approach for effectively process tasks in the cloud environment while maintaining dependency deadline constraints. The suggested model’s aim reduce application’s energy consumption total execution time taking into account limitations. To select VM dynamically deploy/undeploy on hosts based jobs’ requirements, an energy-efficient (EVMP) algorithm presented. Demonstrate proposed outperforms existing PESVMC (power-efficient consolidation) algorithm.