• Vinay K

Scientific workflows generally comprise of fine granular large scale data and require a robust and reliable scheduling techniques. In this paper, a new fault-tolerant scheduling algorithm called Cluster based Heterogeneous Earliest Finish Time (C-HEFT) to enhance the fault tolerance mechanism for SWf in highly distributed cloud environment is proposed. Furthermore, to mitigate the failure of clustered tasks, this algorithm uses idle-time of the provisioned resources to resubmit the failed clustered tasks for successful execution of workflows. Experimental results show that the proposed algorithm has convincing impact on the workflow execution and also drastically reduce the resource waste compared to existing task replication techniques. A trace based simulation of three real SWf shows that the algorithm is able to sustain unexpected task failures with minimal cost and make span.

Cloud Computing, Scientific Workflows, Scheduling, Fault tolerance, Task clustering, Failed tasks

"Dynamic Fault-Tolerant Scheduling for Deadline Constrained Scientific Workflows in the Cloud", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.73-76, June-2019, Available :http://www.jetir.org/papers/JETIR1908763.pdf

"Dynamic Fault-Tolerant Scheduling for Deadline Constrained Scientific Workflows in the Cloud", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp73-76, June-2019, Available at : http://www.jetir.org/papers/JETIR1908763.pdf