A fault-tolerant workflow management system with Quality-of-Service-aware scheduling for scientific workflows in cloud computing

Abstract

Cloud computing provides solutions to many scientific and business applications. Large-scale scientific applications, which are structured as scientific workflows, are evaluated through cloud computing. In this paper, we proposed a Quality-of-Service-aware fault-tolerant workflow management system (QFWMS) for scientific workflows in cloud computing. We have considered two real-time scientific workflows, i.e., Montage and CyberShake, for an evaluation of the proposed QFWMS. The results of the proposed QFWMS scheduling were evaluated through simulation environment WorkflowSim and compared with three well-known heuristic scheduling policies: (a) minimum completion time (MCT), (b) Maximum-minimum (Max-min), and (c) Minimum-minimum (Min-min). By considering Montage scientific workflow, the proposed QFWMS reduces the make-span 8.86%, 8.94%, and 5.53% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 6.19%, 3.52%, and 3.60% compared with existing three heuristic policies. Likewise, by considering CyberShake scientific workflow, the proposed QFWMS reduces the make-span 19.54%, 21.41%, and 25.71% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 8.78%, 8.40%, and 8.61% compared with existing three heuristic policies. More so, for QFWMS, SLA is neither violated for time constraints nor for cost constraints. While for MCT, Max-min and Min-min scheduling policies, SLA is violated 32, 37, and 23 times, respectively. Conclusively, the proposed QFWMS scheduling and management system is one of the significant workflow management systems for execution and management of scientific workflows in cloud computing.