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The Virtual Machine Placement Algorithm Based on Equivalent Resource Model in the Offloading Data Center of Mobile Cloud Environment

机译:基于等效资源模型的移动云环境下卸载数据中心虚拟机布局算法

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In the mobile cloud environment, the massive computing and interchanging tasks are necessary to split and migrate from the mobile terminals to the matched virtual machines in offloading data center. In general, the constant and intensive resource application and virtual machines placement actions probably cause resource fragmentation phenomenon in the physical Servers of data center. The performance overhead seriously constraints the number of parallel load virtual machines and thereby obstructs the global efficiency of offloading system. In this paper, we proposed a novel online virtual machine placement algorithm. Primary, it establishes a virtual machine equivalent peak resource utilization model for one-dimension resource constrained condition, which is on account of historical static data, law of large numbers and given Service Level Agreement(SLA). Secondary, according to the equivalent model, it is able to simplify and convert the placement process to a improved bin packing algorithm via SLA constrained and virtual machine random exchange strategy. Tertiary, based on polling strategy and statistic theory, it builds placement arrangement algorithm for multi-dimension resource condition. Theoretical analysis and numerical simulation demonstrates that the online algorithm is balanceable of the efficient and fairness for virtual machines placement in resource reservation and allocation of one-dimension and multi-dimension condition.
机译:在移动云环境中,需要大量的计算和交换任务才能将其从移动终端拆分并迁移到卸载数据中心中的匹配虚拟机。通常,持续而密集的资源应用程序和虚拟机放置操作可能会在数据中心的物理服务器中引起资源碎片现象。性能开销严重限制了并行负载虚拟机的数量,从而阻碍了卸载系统的整体效率。在本文中,我们提出了一种新颖的在线虚拟机放置算法。首先,它基于历史静态数据,大量定律和给定的服务水平协议(SLA),针对一维资源受限条件建立了一个虚拟机等效峰值资源利用模型。其次,根据等效模型,它可以通过SLA约束和虚拟机随机交换策略简化放置过程并将其转换为改进的装箱算法。第三级,基于轮询策略和统计理论,构建了多维资源条件下的布局安排算法。理论分析和数值模拟表明,该在线算法在虚拟机资源预留,一维和多维条件分配中的有效性和公平性之间是可以平衡的。

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