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Virtual Machine Resource Allocation for Service Hosting on Heterogeneous Distributed Platforms

Abstract : We propose algorithms for allocating multiple resources to competing services running in virtual machines on heterogeneous distributed platforms. We develop a theoretical problem formulation and compare these algorithms via simulation experiments based in part on workload data supplied by Google. Our main finding is that vector packing approaches proposed in the homogeneous case can be extended to provide high-quality solutions in the heterogeneous case, and combined to provide a single efficient algorithm. We also consider the case when there may be errors in estimates of performance-related resource needs. We provide a resource sharing algorithm and prove that for the single-resource, single-node case, when there is no bound on the error, its performance ratio relative to an omniscient optimal algorithm is $\frac{2J-1}{J^2}$, where $J$ is the number of services. We also provide a heuristic approach for compensating for bounded errors in resource need estimates that performs well in simulation.
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Submitted on : Friday, October 21, 2011 - 2:28:58 PM
Last modification on : Friday, November 18, 2022 - 9:24:55 AM
Long-term archiving on: : Thursday, November 15, 2012 - 10:15:54 AM


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  • HAL Id : inria-00634522, version 1


Henri Casanova, Mark Stillwell, Frédéric Vivien. Virtual Machine Resource Allocation for Service Hosting on Heterogeneous Distributed Platforms. [Research Report] RR-7772, INRIA. 2011. ⟨inria-00634522⟩



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