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A combined forecast-based virtual machine migration in cloud data centers

机译:云数据中心的基于预测的基于预测的虚拟机迁移

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Live virtual machine (VM) migration improves the performance of cloud data center in terms of energy efficiency, fault tolerance, and availability. The workload handled by cloud data center is dynamic in nature. This increases the resource requirement of either the migrated virtual machine or collocated virtual machine at any time leading to further migration. Inappropriately handled live VM migration imposes severe application performance degradation. In this paper, a combined forecasting technique to predict the resource requirement of any virtual machine is proposed. Based on the current and predicted resource utilization, live migration is performed by Combined Forecast Load-Aware technique. Experiments were carried out to evaluate the performance of the proposed technique on live VM migration. The outcomes indicate that the proposed approach has minimized the number of migrations, energy usage, and the message overhead when compared with the existing state-of-art technique. (C) 2018 Elsevier Ltd. All rights reserved.
机译:实时虚拟机(VM)迁移在能效,容错和可用性方面提高了云数据中心的性能。云数据中心处理的工作负载本质上是动态的。这会在任何时间都会增加迁移的虚拟机或连接虚拟机的资源需求,从而导致进一步迁移。不恰当地处理Live VM迁移造成严重的应用程序性能下降。在本文中,提出了一种预测预测任何虚拟机的资源需求的组合预测技术。基于当前和预测的资源利用率,通过组合预测负载感知技术执行实时迁移。进行了实验,以评估提出的技术对活VM迁移的性能。结果表明,与现有的最先进技术相比,所提出的方法最小化了迁移,能源使用量和信息开销的数量。 (c)2018年elestvier有限公司保留所有权利。

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