A Framework for Proactive Resource Provisioning in IaaS Clouds - Yi-Hsuan Lee; Kuo-Chan Huang; Cheng-Hsien Wu; Yen-Hsuan Kuo; Kuan-Chou Lai (Applied Sciences, 2017)
Cloud computing is an emerging technology for rapidly provisioning and releasing resources on-demand from a shared resource pool. When big data is analyzed/mined on the cloud platform, the efficiency of resource provisioning would affect the system performance. This work proposes a framework for proactive resource provisioning in IaaS (Infrastructure as a Service) clouds to improve system performance. The proposed framework consists of the virtual cluster computing system, the profiling system, the resource management system, and the monitoring system. In this framework, the over-commit mechanism is applied to improve resource utilization. Furthermore, a proactive task scheduling approach is also present to prevent the postponement of tasks in critical stages, especially when the amount of aggregated resources requested by virtual machines exceeds that of available resources on the over-committed physical machines. Experimental results show that the over-commit approach indeed improves the resource utilization. However, when the degree of applying the over-commit approach increases, the burden of this proposed approach also conceivably increases. Therefore, the proposed framework further applies the proactive task scheduling approach to execute the time-critical tasks earlier to shorten the processing time. A small-scale cloud system including 3 servers is built for experiments. Preliminary experimental results show the performance improvement of our proposed framework in IaaS clouds.