A workflow based approach for task scheduling in cloud environment

A Cloud computing environment provides a huge repository of computing resources which can be utilized for executing user tasks over the Internet. One of the challenges in such a computing paradigm is the optimal use of resources both from the cloud provider as well as consumer's point of view. Techniques have been developed to execute tasks with different level of complexity and size by assigning the tasks to the available resource pool which may span over a large geographical area. In this paper, we suggested a workflow approach to execute large number of interdependent tasks using a set of computing resources with heterogeneous capacity. The objective of this work is to allocate the tasks in such a way that the total time required to complete is minimized. The proposed technique is an extension of max–min algorithm applied on a Directed Acyclic Graph representing a set of interdependent tasks. The technique has been tested on standard scientific workflows and the results are found to be better compared to other similar works in terms of makespan. © 2021