An efficient task scheduling algorithm for heterogeneous multi-cloud environment

Cloud Computing has been adopted as one of the growing technologies in the business and research community. However, due to significant client demands, there is a need to overflow some workloads to other data centers as no data center has unlimited resources. The workload sharing provides even more flexible and cheaper resources to complete the applications submitted to the data centers. However, scheduling workloads in multi-cloud environment is challenging as the data centers have resources which are heterogeneous in nature. In this paper, we propose a task scheduling algorithm in a heterogeneous multi-cloud environment. The algorithm is based on two popular algorithms namely, Min-Min and Max-Min. We perform extensive experiments on some benchmark and synthetic data sets and compare the results with two existing multi-cloud scheduling algorithms. The results show that the proposed algorithm outperforms both the algorithms in terms of makespan and average cloud utilization.