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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hadji, M. Zeghlache, D. |
| Copyright Year | 2012 |
| Abstract | A minimum cost maximum flow algorithm is proposed for resources(e.g. virtual machines) placement in clouds confronted to dynamic workloads and flows variations. The algorithm is compared to an exact method generalizing the classical Bin-Packing formulation using a linear integer program. A directed graph is used to model the allocation problem for cloud resources organized in a finite number of resource types; a common practice in cloud services. Providers can use the minimum cost maximum flow algorithm to opportunistically select the most appropriate physical resources toserve applications or to ensure elastic platform provisioning. The modified Bin-Packing algorithm is used to benchmark the minimum cost maximum flow solution. The latter combined with a prediction mechanism to handle dynamic variations achieves near optimal performance. |
| Starting Page | 876 |
| Ending Page | 882 |
| File Size | 367593 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781467328920 |
| ISSN | 21596190 |
| DOI | 10.1109/CLOUD.2012.36 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-24 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Cloud Computing Heuristic algorithms Minimum Cost Maximum Flow Resource Allocation Predictive models Prediction algorithms Dynamic scheduling Virtual machining Linear Integer Programming Resource management |
| Content Type | Text |
| Resource Type | Article |
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