Using imbalance characteristic for fault-tolerant workflow scheduling in Cloud systems - 2017 PROJECT TITLE : Using imbalance characteristic for fault-tolerant workflow scheduling in Cloud systems - 2017 ABSTRACT: Resubmission and replication are 2 fundamental and widely recognized techniques in distributed computing systems for fault tolerance. The resubmission based strategy has an advantage in resource utilization, while the replication based mostly strategy will cut back the task completed time in the context of fault. However, few researches take these two techniques together for fault-tolerant workflow scheduling, particularly in Cloud systems. During this paper, we present a novel fault-tolerant workflow scheduling (ICFWS) algorithm for Cloud systems by combining the aforementioned two ways together to play their respective benefits for fault tolerance whereas trying to fulfill the soft deadline of workflow. First, it divides the soft deadline of workflow into multiple sub-deadlines for all tasks. Then, it selects a affordable fault-tolerant strategy and reserves appropriate resource for each task by taking the imbalance sub-deadlines among tasks and on-demand resource provisioning of Cloud systems into consideration. Finally, an on-line scheduling and reservation adjustment theme is intended to select a appropriate resource for the task with resubmission strategy and change the sub-deadlines and fault-tolerant strategies of some unexecuted tasks throughout the task execution method, respectively. The proposed algorithm is evaluated on both real-world and randomly generated workflows. The results demonstrate that the ICFWS outperforms some well-known approaches on corresponding metrics. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Dynamic Outsourced Auditing Services for Cloud Storage Based on Batch-Leaves- Authenticated Merkle Hash Tree - 2017 Scheduling for Workflows with Security-Sensitive Intermediate Data by Selective Tasks Duplication in Clouds - 2017