Adaptive and Convex Optimization-Inspired Workflow Scheduling for Cloud Environment

Scheduling large-scale and resource-intensive workflows in cloud infrastructure is one of the main challenges for service providers (CSPs). Cloud more efficient when virtual machines other resources work up to their full potential. The factor that influences quality services distribution workflow on (VMs). tasks VMs depends type mechanism resource allocation. Scientific include data transfer consume intensive infrastructures. Therefore, scheduling from scientific requires optimized techniques. This paper proposes an optimised approach aims improve utilization without increasing execution time cost.