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Availability-Aware and Energy-Efficient Virtual Cluster Allocation Based on Multi-Objective Optimization in Cloud Datacenters

机译:基于云数据中心多目标优化的可用性感知和节能虚拟群集分配

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摘要

With greater numbers of cloud applications being deployed in virtual clusters (VCs) and running in datacenters, the energy consumption of datacenters is experiencing rapidly cumulative growth. Thus, it is a critical issue that how to allocate virtual machines (VMs) of the VC in physical machines (PMs) for energy savings as much as possible. Considering each PM/switch has a certain failure rate, VMs may not be executed when they meet with any PM/switch fault. So, a compact allocation scheme may benefit in low energy consumption but increase the risk of violating the availability of the VC. In this paper, we consider four optimization objectives about the VC and the datacenter, i.e., availability, energy consumption, average resource utilization, and resource load balance. Then we propose a multi-objective optimization model and raise an evolution algorithm to trade-off among these four optimization objectives. Finally, experimental results show the effectiveness and efficiency of our algorithm.
机译:具有更多云应用程序在虚拟群集(VCS)中部署并在数据中心运行,数据中心的能耗正在经历迅速累积增长。因此,这是一种关键问题,即如何尽可能地为物理机器(PMS)中的虚拟机(VM)分配虚拟机(VM)以节省能量。考虑到每个PM /交换机都有一定的故障率,在符合任何PM / SPREFE故障时可能无法执行VM。因此,紧凑的分配方案可能会在低能量消耗中受益,但增加违反VC可用性的风险。在本文中,我们考虑了关于VC和数据中心的四个优化目标,即可用性,能耗,平均资源利用率和资源负载平衡。然后,我们提出了一种多目标优化模型,并在这四个优化目标中提高进化算法在权衡。最后,实验结果表明了我们算法的有效性和效率。

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