Deadline-Constrained Cost Minimisation for Cloud Computing Environments
Samuel Manam, Klaus Moessner, Serdar Vural · IEEE Access · 2023
The interest in performing scientific computations using commercially available cloud computing resources has grown rapidly in the last decade. However, scheduling multiple workflows in cloud computing is challenging due to its non-functional constraints and multi-dimensional resource requirements. Scheduling algorithms proposed in literature use search-based approaches which often result in very high computational overhead and long execution time. In this paper, a Deadline-Constrained Cost Minimisation (DCCM) algorithm is proposed for resource scheduling in cloud computing. In the proposed scheme, tasks are grouped based on their scheduling deadline constraints and data dependencies. Compared to other approaches, DCCM focuses on meeting the user-defined deadline by sub-dividing tasks into different levels based on their priorities. Simulation results show that DCCM achieves higher success rate when compared to the state-of-the-art approaches.