Optimal Virtual Machines allocation in mobile femto-cloud computing: An MDP approach

Valerio Di Valerio, F. L. Presti
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引用次数: 25

Abstract

Offloading to external surrogate machines (part of) the workload generated by applications running on mobile nodes has been suggested as a way to improve the mobile user experience. In this paper, we consider a set of mobile users that can offload their computation on Virtual Machines (VMs) instantiated in a cloud infrastructure implemented over a set of femtocells which have been augmented with computational resources. In this setting, a critical task is to determine where users VMs should be allocated across the different femtocells as to optimize the user performance. In this paper we formulate the VMs allocation problem as a Markov Decision Process (MDP) based optimization, to directly take into account the system dynamics and optimize the long term performance. The optimal policy is obtained solving the MDP using a Linear Programming reformulation. We illustrate the behavior of the proposed policy in simple scenarios.
移动云计算中的最优虚拟机分配:一种MDP方法
有人建议将运行在移动节点上的应用程序生成的工作负载卸载到外部代理机器(部分),以改善移动用户体验。在本文中,我们考虑了一组移动用户,他们可以在云基础设施中实例化的虚拟机(vm)上卸载他们的计算,这些虚拟机实现在一组已经增强了计算资源的移动蜂窝上。在这种设置中,一项关键任务是确定应该在不同的基站之间将用户vm分配到何处,以优化用户性能。本文将虚拟机分配问题表述为一个基于马尔可夫决策过程(MDP)的优化问题,以直接考虑系统动态并优化长期性能。利用线性规划的重新表述,得到了求解MDP的最优策略。我们将在简单的场景中演示所建议策略的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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