Hybrid Cloud Resource Scheduling With Multi-dimensional Configuration Requirements

Abstract

Task scheduling with multi-dimensional configuration requirements is widely used in cloud platforms such as OpenStack and Kubernetes. In this paper, we consider the problem of scheduling tasks with multi-dimensional configuration to hybrid resources. An energy-aware scheduling algorithm on tasks with multi-dimensional configuration requirements (ESMCR in short) is presented. ESMCR is combined with a decomposition-based multi-objective evolutionary algorithm to minimize energy consumption and provide sufficient capacity for the data center. An entropy-based performance index is modeled to measure the QoS. The experimental results indicate that the proposed algorithms outperform the compared algorithms significantly.