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Two of the essential components of cloud computing are high-performance computing and mass storage, and when compared to other conventional distributed systems, cloud computing offers both components on a more accessible, elastic, and scalable platform. Due to disaster in the cloud, the stored data will be lost. To avoid this problem, replica management-based data transfer scheduling is proposed in this paper. For the scheduling process, the adaptive sunflower optimization (ASFO) algorithm is used which is selecting the optimal path among the number of paths. The selected path should be taken at a minimum distance. The entire work consists of solution encoding, fitness evaluation, and updation. The effectiveness of the suggested methodology is evaluated using response time, turnaround time, and waiting time, and our suggested method also produces better outcomes when compared to other methods.