Fast and energy-aware resource provisioning and task scheduling for cloud systems
Cloud computing has become an attractive computing paradigm in recent years to offer on demand computing resources for users worldwide. Through Virtual Machine (VM) technologies, the cloud service providers (CSPs) can provide users the infrastructure, platform, and software with a quite low cost. With the drastically growing number of data centers, the energy efficiency has drawn a global attention as CSPs are faced with the high energy cost of data centers. Many previous works have contributed to improving the energy efficiency in data centers. However, the computational complexity may lead to unacceptable run time. In this paper, we propose a fast and energy-aware resource provisioning and task scheduling algorithm to achieve low energy cost with reduced computational complexity for CSPs. In our iterative algorithm, we divide the provisioning and scheduling to multiple steps which can effectively reduce the complexity and minimize the run time while achieving a reasonable energy cost. Experimental results demonstrate that compared to the baseline algorithm, the proposed algorithm can achieve up to 79.94% runtime improvement with an acceptable energy cost increase.