Cloud service providers use load balancing algorithms in order to avoid Service Level Agreement Violations (SLAVs) and wasted energy consumption due to host over- and under-utilization, respectively. Load balancing algorithms migrate VMs between hosts in order to balance host loads. Any Virtual Machines (VMs) that are migrated experience performance degradation which results in lower Quality of Service (QoS) and can possibly result in SLAVs. Hence, an optimal load balancing method should reduce the number of over- and under-utilized hosts with a minimal number of VM migrations. One of the metrics used previously in the literature for evaluating load balancing stated that it equally considered SLAVs caused by both over-utilized hosts and migrations. However, in this paper, we show that, in fact, this metric values keeping the number of migrations low at the expense of an increased number of over-utilized hosts. This disparity is demonstrated by simulation of Google, PlanetLab and Azure data sets in CloudSim. This metric may suit public cloud providers which are focused on minimizing SLAVs and keeping energy costs low, but does not consider the QoS of customer VMs. We propose an alternative metric that considers QoS for the VMs. This alternative metric considers not only performance loss during migration, but also performance degradation due to host over-utilization. Private cloud providers, e.g., IT services within large organizations, often value the performance of their “customer” VMs, i.e., the QoS their organization receives, as well as traditional cloud provider costs, i.e., energy and SLAV costs. Hence, our alternative metric would be more appropriate in these scenarios. We compare and contrast load balancing methods using both the existing, biased metric and our new alternative metric.

云服务提供商使用负载平衡算法，以避免分别由于主机利用率过高和利用率不足而造成的服务水平协议违规（SLAV）和能源浪费。负载平衡算法在主机之间迁移VM，以平衡主机负载。迁移的任何虚拟机（VM）都会出现性能下降，这会导致服务质量（QoS）降低，并可能导致SLAV。因此，最佳的负载平衡方法应以最少的VM迁移次数减少过度使用和未充分利用的主机的数量。先前文献中用于评估负载平衡的一种度量标准表示，它同样考虑了过度使用主机和迁移造成的SLAV。但是，在本文中，我们表明，实际上，此指标值使迁移数量保持较低，但以增加过度使用的主机数量为代价。通过在CloudSim中对Google，PlanetLab和Azure数据集进行仿真证明了这种差异。该指标可能适合专注于最小化SLAV并保持较低能源成本的公共云提供商，但并未考虑客户VM的QoS。我们提出了一种替代指标，该指标考虑了VM的QoS。此替代指标不仅考虑迁移期间的性能损失，还考虑由于主机过度使用而导致的性能下降。私有云提供商，例如大型组织中的IT服务，通常会重视其“客户” VM的性能，即组织所获得的QoS，以及传统云提供商的成本（即能源和SLAV成本）。因此，在这些情况下，我们的替代指标会更合适。我们使用现有的偏差指标和新的替代指标来比较和对比负载平衡方法。