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An energy optimization with improved QOS approach for adaptive cloud resources

机译:改进自适应云资源QoS方法的能量优化

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In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.
机译:最近,由于在此云计算VMS中,我们的日常生活中,在日常生活中,在日常生活中的利用率极大地增强了云计算VMS的利用率在此云计算VMS中可以使用众多不同的方案如多媒体信号处理方法实现。因此,这些云计算VM的有效性能成为必要约束,精确地用于这些多媒体信号处理方法。然而,这些云计算VM的大量能耗和降低效率是不同云计算组织所面临的关键问题。因此,在这里,我们引入了基于动态电压和频率缩放(DVFS)的自适应云资源重新配置(ACRR)技术,用于云计算设备,其有效地降低了能量消耗,以及在更短时间内执行操作。我们已经证明了一种有效的资源分配和利用技术来通过降低模型的不同成本来优化。我们还通过减少任务负载来展示有效的能量优化技术。我们的实验结果显示了我们提出的模型ACRR的优越性,在平均运行时间,功耗和比任何其他最先进技术所需的平均功率。

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