A planned scheduling process of cloud computing by an effective job allocation and fault-tolerant mechanism

In the scientific world, cloud computing is utilized for several applications like financial, healthcare biomedical systems, and so on. However, the chief drawback behind in cloud computing paradigm is if any one of the hosts failed during the data transmission then it interrupts the whole process. To overcome this problem the current research proposed a novel Hybrid Grey Wolf and Ant Lion Model (HGW–ALM) with lively standby replication (LSR) strategy to enhance the cloud computing paradigm. In addition, if any one of the hosts has less capacity than its workload, then that particular host is predicted by the HGW–ALM model and the specified host is maintained by the LSR approach. Moreover, the checkpoint strategy is efficiently processed with the tolerant mechanism. In addition, the discussed faults in this present article were virtual machine failure faults, timing faults, and response faults. Also, the robustness of the proposed algorithm is checked against few attacks like replay, Denial of service and data injection attacks. Subsequently, the drawn charts, graphs, and tables proved the efficiency of the proposed work by comparing key metrics with existing approaches. Thus, the proposed frame model achieved a better result by obtaining high throughput as 6000 bps, resource usage only 20% and less makespan time 200 s.