A Critical Review of Workflow Scheduling Algorithms in Cloud Computing Environment

Cloud computing has gained so much of attention due to its features such as pay-per-use basis, resource pooling, and scalability that has forced the professionals to use cloud services for executing various applications. The cloud resources are now used to execute scientific workflow applications, where each task (node) is directed to other task (node) through a path (edge) that represents the flow data from one node to another known as workflows. To map these workflows to cloud resources various workflow scheduling strategies has been adopted based on budget and deadline constraints. In this article we have accomplished a review on existing workflow scheduling algorithms implemented in cloud environment that are capable to reduce cost, makespan, increase resource utilization, etc. under a budget or deadline constraint [1][2].