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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pei Fan Zhenbang Chen Ji Wang Zibin Zheng |
| Copyright Year | 2012 |
| Abstract | Infrastructure-as-a-Service (IaaS) clouds provide on-demand virtual machines (VMs) to users. How to improve the quality of IaaS cloud services is important for service providers. Currently, the VMs in an IaaS cloud are usually deployed with respect to the maximum utilization of resources. In this paper, we propose an online VM optimization method for IaaS clouds. Our method mainly optimizes the VM deployment in IaaS clouds according to the traffics among VMs. VMs are allocated with respect to cabinet capacities at the beginning. At runtime, we monitor the traffics among VMs to get the traffic topology, based on which related VMs are migrated to neighbors to improve performance and reduce the traffics across cabinets. Preliminary simulation experiments are conducted on a well-know simulator, and the experimental results indicate that our method is effective and promising. |
| Starting Page | 760 |
| Ending Page | 765 |
| File Size | 422044 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467345651 |
| ISSN | 15219097 |
| e-ISBN | 9780769549033 |
| DOI | 10.1109/ICPADS.2012.123 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-12-17 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Runtime Topology Monitoring Optimization Clustering algorithms Bandwidth Cloud computing virtual machine IaaS cloud deployment online optimization traffic topology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Hardware and Architecture |
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