The rapid development of cloud computing with virtualization technology has benefited both academia and industry. For any cloud data center at scale, one of the primary challenges is how to effectively orchestrate a large number of virtual machines (VMs) in a performance-aware and cost-effective manner. A key problem here is that the performance interference between VMs can significantly undermine the efficiency of cloud data centers, leading to performance degradation and additional operation cost. To address this issue, extensive studies have been conducted to investigate the problem from different aspects. In this survey, we make a comprehensive investigation into the causes of VM interference and provide an in-depth review of existing research and solutions in the literature. We first categorize existing studies on interference models according to their modeling objectives, metrics used, and modeling methods. Then we revisit interference-aware strategies for scheduling optimization as well as co-optimization-based approaches. Finally, the survey identifies open challenges with respect to VM interference in data centers and discusses possible research directions to provide insights for future research in the area.

云计算与虚拟化技术的快速发展使学术界和工业界都受益匪浅。对于任何大规模的云数据中心，主要挑战之一是如何以性能感知和具有成本效益的方式有效地编排大量虚拟机 (VM)。这里的一个关键问题是 VM 之间的性能干扰会严重破坏云数据中心的效率，从而导致性能下降和额外的运营成本。为了解决这个问题，已经进行了广泛的研究，从不同方面调查这个问题。在本次调查中，我们对 VM 干扰的原因进行了全面调查，并对文献中的现有研究和解决方案进行了深入审查。我们首先根据其建模目标、使用的指标和建模方法对干扰模型的现有研究进行分类。然后我们重新审视用于调度优化的干扰感知策略以及基于协同优化的方法。最后，该调查确定了数据中心 VM 干扰方面的开放挑战，并讨论了可能的研究方向，为该领域的未来研究提供见解。