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Migration energy-aware workload consolidation in enterprise clouds

机译:在企业云中迁移能源意识的工作负载整合

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Consolidation through live VM migrations is a promising approach to improve server utilization. However, prior consolidation works have focused mostly on the performance impact of migration and neglected the associated energy overhead. Our research finds that energy impact of migration can offset over 12 % of the energy saved through energy-conscious workload packing. To address this limitation of the current state of research, in this paper we devise new schemes to pack applications that targets a joint optimization of energy and performance overhead of VM migrations. Additionally, we develop a statistical workload modeling technique for simulating consolidation problem in enterprise cloud contexts. Our experiments with statistically generated synthetic trace and Google's production trace demonstrate that our schemes can improve energy savings up to 23% compared to state of the art power-aware workload consolidation strategy.
机译:通过实时VM迁移进行整合是提高服务器利用率的一种有前途的方法。但是,先前的合并工作主要集中在迁移对性能的影响上,而忽略了相关的能源开销。我们的研究发现,迁移对能源的影响可以抵消因节约能源而造成的工作量减少所节省的能源的12%。为了解决当前研究现状的局限性,在本文中,我们设计了新的方案来打包应用程序,这些应用程序旨在共同优化VM迁移的能源和性能开销。此外,我们开发了一种统计工作量建模技术,用于在企业云环境中模拟合并问题。我们使用统计生成的合成迹线和Google的生产迹线进行的实验表明,与最先进的功耗感知工作负载整合策略相比,我们的方案最多可将能源节省提高23%。

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