An Integrated Dynamic Resource Scheduling Framework in On-Demand Clouds
The biggest advantage of employing virtualization in cloud is the ability to provision resource flexibly which makes "pay-as-use" model possible. However, since the workload of virtual machine constantly changes, it is still a challenge that efficiently schedule resource by migrating virtu...
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| Veröffentlicht in: | Journal of Information Science and Engineering 2014-09, Vol.30 (5), p.1537-1552 |
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| container_title | Journal of Information Science and Engineering |
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| creator | 徐磊(Lei Xu) 王总辉(Zong-Hui Wang) 陈文智(Wen-Zhi Chen) |
| description | The biggest advantage of employing virtualization in cloud is the ability to provision resource flexibly which makes "pay-as-use" model possible. However, since the workload of virtual machine constantly changes, it is still a challenge that efficiently schedule resource by migrating virtual machines among lots of hosts, especially with multi-objective to meet, like power and QoS constraints. In this paper, we present a dynamic resource scheduling solution, named Smart-DRS, which can well determines when to schedule, which to schedule, and where to schedule. It is an integrated framework that aims to deal well with hotspot mitigation, load balancing and server consolidation which are classic problems to solve in on-demand clouds. The experimental results show that our framework strikes a balance between efficiency, overhead and instantaneity. |
| doi_str_mv | 10.6688/JISE.2014.30.5.13 |
| format | Article |
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| ispartof | Journal of Information Science and Engineering, 2014-09, Vol.30 (5), p.1537-1552 |
| issn | 1016-2364 |
| language | eng |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Applied sciences Balancing Clouds Computer science control theory systems Computer systems and distributed systems. User interface Consolidation Dynamics Exact sciences and technology Resource scheduling Schedules Software Strikes Virtual environments Workload |
| title | An Integrated Dynamic Resource Scheduling Framework in On-Demand Clouds |
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