A Novel Task Scheduling Algorithm in Heterogeneous Multi-cloud Environment

The NP-complete problem of task scheduling in a heterogeneous multi-cloud context is well-known. To manage workloads, cloud providers must implement an effective task scheduling algorithm due to the exponential growth of client applications. In addition, to prevent demand fluctuations, the cloud provider might need to work in conjunction with other cloud providers. The heterogeneous multi-cloud task scheduling challenge is the name given to this workload-sharing issue. This paper presents an independent task scheduling technique for a multi-cloud heterogeneous environment in this paper. It organizes tasks based on the combination of random group formation followed by min-min task allocation. The paper also presents thorough tests on benchmark and synthetic datasets, comparing the outcomes with popular algorithms CMMS, SBTS, and CMAXMS. The comparison results demonstrate the suggested algorithm’s outcomes in terms of two assessment metrics like makespan and average cloud utilization.