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2012 IEEE Fifth International Conference on Cloud Computing
Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds
Honolulu, HI, USA USA
June 24-June 29
ISBN: 978-1-4673-2892-0
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.
Index Terms:
Heuristic algorithms,Resource management,Prediction algorithms,Dynamic scheduling,Virtual machining,Predictive models,Algorithm design and analysis,Minimum Cost Maximum Flow,Cloud Computing,Resource Allocation,Linear Integer Programming
Citation:
Makhlouf Hadji, Djamal Zeghlache, "Minimum Cost Maximum Flow Algorithm for Dynamic Resource Allocation in Clouds," cloud, pp.876-882, 2012 IEEE Fifth International Conference on Cloud Computing, 2012
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