A Linear Swarm – Based Intelligence for Resource Allocation and Fault Prediction in Cloud

The widespread utilization Cloud Computing (CC) services for hosting real-time applications have led to the appearance of service dependability as an essential issue in both users and Cloud Service Providers (CSP). Two diverse fault tolerant approaches are provided to improve the cloud service reliability known as proactive and reactive model. Various prevailing approaches consider the coordination problem among the Virtual Machines (VMs) executes parallel processing. Devoid of appropriate VM coordination, the parallel processing outcomes are not so appropriate. To handle this issue, a VM-based cluster allocation model is designed to diminish the total resource consumption by the data centers and network resources. Here, the VM migration process is performed for deteriorating PM to certain optimal PMs. At last, the optimal target selection is handled with an improved optimization approach known as linear Swarm-based intelligence. Here, various metrics are evaluated and compared with other approaches. The experimental outcomes illustrate the efficiency of the anticipated model.