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Energy efficient power aware VM scheduling in decentralized cloud

机译:分散式云中的节能高效节能VM调度

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The increase in the popularity of cloud computing paradigm in the recent years has led to the rapid expansion of datacenters which involves deploying more number of software networks and remote servers that allow centralized storage of data and online access to the services or its resources. In spite of its advantage of reduced energy consumption at the user's end, managing the increase in demand, optimal energy efficiency and satisfying high performance expectations of users must be taken care at the cloud provider's end. In this paper, we propose a decentralized Power Aware Best Fit Priority algorithm that allocates the requested virtual machines to the hosts whose increase in the power consumption factor is minimal. We also handle the host overloading and underloading scenarios by including the concept of “skewness” to detect the uneven utilization of servers and by adopting Median Absolute Deviation(MAD) policy to dynamically set the upper and lower thresholds for VM consolidation.
机译:近年来,云计算范例的日益普及导致数据中心的迅速扩展,这涉及部署更多数量的软件网络和远程服务器,以允许集中存储数据以及在线访问服务或其资源。尽管它具有减少用户端能耗的优势,但在云提供商的端头必须注意管理需求的增长,最佳能效和满足用户的高性能期望。在本文中,我们提出了一种分散的Power Aware Best Fit Priority算法,该算法将请求的虚拟机分配给功耗因数增加最小的主机。我们还通过包含“偏斜度”概念来检测服务器利用率的不平衡以及采用中位数绝对偏差(MAD)策略来动态设置VM整合的上限和下限,来处理主机过载和负载不足的情况。

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