A New Fault-Tolerant Algorithm Based on Replication and Preemptive Migration in Cloud Computing

Abstract

Cloud computing is a promising paradigm that provides users higher computation advantages in terms of cost, flexibility, and availability. Nevertheless, with potentially thousands of connected machines, faults become more frequent. Consequently, fault-tolerant load balancing becomes necessary in order to optimize resources utilization while ensuring the reliability of the system. Common fault tolerance techniques in cloud computing have been proposed in the literature. However, they suffer from several shortcomings: some fault tolerance techniques use checkpoint-recovery which increases the average waiting time and thus the mean response time. While other models rely on task replication which reduces the cloud's efficiency in terms of resource utilization under variable loads. To address these deficiencies, an efficient and adaptive fault tolerant algorithm for load balancing is proposed. Based on the CloudSim simulator, some series of test-bed scenarios are considered to assess the behavior of the proposed algorithm.

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

“…This approach also uses a failure predictor module to foresee whether a failure may occur shortly or not. Hakem et al in Reference 141 presented combination of reactive, that is, replication and proactive, that is, preemptive migration fault tolerance approaches. This approach employs preemptive migration and replication to proactively prevent failures and reactively mitigate the impact of failed virtual machines (VMs).…”