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Cloud computing has become a popular paradigm for providing on-demand computing resources over the internet. Efficient resource utilization is critical for cloud service providers to maximize profit and meet quality of service requirements. However, the heterogeneity and dynamism of cloud environments make efficient resource allocation challenging. In this paper, we propose a fault-tolerant heuristic task scheduling algorithm to optimize resource utilization in cloud computing environments. The algorithm employs both replication and migration techniques to provide fault tolerance while minimizing makespan and balancing load across resources. Simulation experiments demonstrate that our algorithm achieves up to 13 \% improvement in resource utilization compared to benchmark algorithms under various fault-prone scenarios. The results confirm the effectiveness of the proposed algorithm in enhancing resource efficiency and sustaining performance during resource failures.
Chawla et al. (Thu,) studied this question.