Research Area:  Cloud Computing
In recent days most of the enterprises and communities adopt cloud services to deploy their workflow-based applications due to the inherent benefits of cloud-based services. These workflow-based applications are mainly compute-intensive. The major issues of workflow deployment in a cloud environment are minimizing execution time (makespan) and monetary cost. As cloud service providers maintain adequate infrastructural resources, workflow scheduling in the cloud environment becomes a non-trivial task. Hence, in this paper, we propose a scheduling technique where monetary cost is reduced, while workflow gets completed within its minimum makespan. To analyze the performance of the proposed algorithm, the experiment is carried out in WorkflowSim and compares the results with the existing well-known algorithms, Heterogeneous Earliest Finish Time (HEFT) and Dynamic Heterogeneous Earliest Finish Time (DHEFT). In all the experiments, the proposed algorithm outperforms the existing ones.
Author(s) Name:  Kamalesh Karmakar,Rajib K Das,Sunirmal Khatua
Conferrence name:  Distributed Computing and Internet Technology
Publisher name:  Springer
Volume Information:  pp 214-226
Paper Link:   https://link.springer.com/chapter/10.1007/978-3-030-36987-3_13