A Framework for Proactive Resource Provisioning in IaaS Clouds
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 pro...
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doaj-ef903dba9fe74c99b07cd1e89fd78fc32020-11-25T00:09:35ZengMDPI AGApplied Sciences2076-34172017-07-017877710.3390/app7080777app7080777A Framework for Proactive Resource Provisioning in IaaS CloudsYi-Hsuan Lee0Kuo-Chan Huang1Cheng-Hsien Wu2Yen-Hsuan Kuo3Kuan-Chou Lai4Department of Computer Science, National Taichung University of Education, Taichung 40306, TaiwanDepartment of Computer Science, National Taichung University of Education, Taichung 40306, TaiwanDepartment of Computer Science, National Taichung University of Education, Taichung 40306, TaiwanDepartment of Computer Science, National Taichung University of Education, Taichung 40306, TaiwanDepartment of Computer Science, National Taichung University of Education, Taichung 40306, TaiwanCloud 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.https://www.mdpi.com/2076-3417/7/8/777over-commitresource provisioningIaaScloud computingcritical pathtask schedulingdata stream computing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi-Hsuan Lee Kuo-Chan Huang Cheng-Hsien Wu Yen-Hsuan Kuo Kuan-Chou Lai |
spellingShingle |
Yi-Hsuan Lee Kuo-Chan Huang Cheng-Hsien Wu Yen-Hsuan Kuo Kuan-Chou Lai A Framework for Proactive Resource Provisioning in IaaS Clouds Applied Sciences over-commit resource provisioning IaaS cloud computing critical path task scheduling data stream computing |
author_facet |
Yi-Hsuan Lee Kuo-Chan Huang Cheng-Hsien Wu Yen-Hsuan Kuo Kuan-Chou Lai |
author_sort |
Yi-Hsuan Lee |
title |
A Framework for Proactive Resource Provisioning in IaaS Clouds |
title_short |
A Framework for Proactive Resource Provisioning in IaaS Clouds |
title_full |
A Framework for Proactive Resource Provisioning in IaaS Clouds |
title_fullStr |
A Framework for Proactive Resource Provisioning in IaaS Clouds |
title_full_unstemmed |
A Framework for Proactive Resource Provisioning in IaaS Clouds |
title_sort |
framework for proactive resource provisioning in iaas clouds |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2017-07-01 |
description |
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. |
topic |
over-commit resource provisioning IaaS cloud computing critical path task scheduling data stream computing |
url |
https://www.mdpi.com/2076-3417/7/8/777 |
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