云计算中的双阈值能量感知负载均衡

Jayant Adhikari, S. Patil
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引用次数: 40

摘要

如今,本地云的实现很流行,组织开始意识到未利用资源所消耗的能量。降低功耗已成为云环境的基本要求,不仅可以降低运营成本,还可以提高系统可靠性。能量感知计算不仅是为了使算法尽可能快地运行,而且是为了最小化计算的能量需求。我们的DT-PALB(双阈值能量感知负载均衡)算法维护所有计算节点的状态,并根据利用率百分比决定应该运行的计算节点数量。我们表明,与使用功耗感知的负载平衡技术相比,我们的解决方案为计算节点资源提供了足够的可用性,同时降低了本地云消耗的总体功耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Double threshold energy aware load balancing in cloud computing
Nowadays implementation of local cloud is popular, organization are becoming aware of power consumed by unutilized resources. Reducing power consumption has been an essential requirement for cloud environments not only to decrease operating cost but also improve the system reliability. The energy-aware computing is not just to make algorithms run as fast as possible, but also to minimize energy requirements for computation. Our DT-PALB (Double Threshold Energy Aware Load Balancing) algorithm maintains the state of all compute nodes, and based on utilization percentages, decides the number of compute nodes that should be operating. We show that our solution provides adequate availability to compute node resources while decreasing the overall power consumed by the local cloud as compared to using load balancing techniques that are power aware.
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