Abstract-Reliability requirement is one of the most important quality of services (QoS) and should be satisfied for a reliable workflow 6 in cloud computing. Primary-backup replication is an important software fault-tolerant technique used to satisfy reliability requirement. Recent works studied quantitative fault-tolerant scheduling to reduce execution cost by minimizing the number of replicas while 8 satisfying the reliability requirement of a workflow on heterogeneous infrastructure as a service (IaaS) clouds. However, a minimum 9 number of replicas does not necessarily lead to the minimum execution cost and shortest schedule length in a heterogeneous IaaS 10 cloud. In this study, we propose the quantitative fault-tolerant scheduling algorithms QFEC and QFEC+ with minimum execution costs 11 and QFSL and QFSL+ with shortest schedule lengths while satisfing the reliability requirements of workflows. Extensive experimental 12 results show that (1) compared with the state-of-the-art algorithms, the proposed algorithms achieve less execution cost and shorter 13 schedule length, although the number of replicas are not minimum; (2) QFEC and QFEC+ are designed to reduce execution cost, and 14 QFEC+ is better than QFEC for all low-parallelism and high-parallelism workflows; and (3) QFSL and QFSL+ are designed to decrease 15 schedule length, and QFSL+ is better than QFSL for all low-parallelism and high-parallelism workflows. Index Terms-Infrastructure as a service (IaaS)
In REF fault tolerant scheduling to enhance the reliability of tasks is proposed.
Quantitative Fault-tolerance for Reliable Workflows on Heterogeneous IaaS Clouds
IEEE Transactions on Cloud Computing
Computer Science