Next Article in Journal
Mechanical Resilience of Modified Bitumen at Different Cooling Rates: A Rheological and Atomic Force Microscopy Investigation
Next Article in Special Issue
Enhancement of Sea Wave Potential Energy with Under-Sea Periodic Structures: A Simulation and Laboratory Study
Previous Article in Journal
An Improved Dispatching Method (a-HPDB) for Automated Material Handling System with Active Rolling Belt for 450 mm Wafer Fabrication
Previous Article in Special Issue
Development of a Modelling and Simulation Method for Residential Electricity Consumption Analysis in a Community Microgrid System
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(8), 777;

A Framework for Proactive Resource Provisioning in IaaS Clouds

Department of Computer Science, National Taichung University of Education, Taichung 40306, Taiwan
Author to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 23 July 2017 / Accepted: 26 July 2017 / Published: 31 July 2017
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2017)
Full-Text   |   PDF [6495 KB, uploaded 31 July 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. View Full-Text
Keywords: over-commit; resource provisioning; IaaS; cloud computing; critical path; task scheduling; data stream computing over-commit; resource provisioning; IaaS; cloud computing; critical path; task scheduling; data stream computing

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Lee, Y.-H.; Huang, K.-C.; Wu, C.-H.; Kuo, Y.-H.; Lai, K.-C. A Framework for Proactive Resource Provisioning in IaaS Clouds. Appl. Sci. 2017, 7, 777.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top