The explosive growth of cloud usage encourages several challenges, especially high energy consumption of Cloud Data Centers (CDCs), new security risks to Virtual Machines (VMs) resulting from co-residency with other risky VMs on the same Physical Machine (PM), and the Quality of Service (QoS) degradation due to sharing resources. Many recent studies have proposed Dynamic VM Consolidation (DVMC) to save energy with minimum degradation of the QoS. However, due to the lack of reliable security measurements and consolidating VMs without any awareness of their security risk degrees, the overall security risk of the CDC may be increased. To tackle these challenges, this study presents a Security-aware DVMC (SDVMC) that consists of a Security Monitoring Module (SMM) and a SDVMC module. The SMM utilizes a three-dimensional security assessment model, while in the SDVMC module we propose a novel VM placement algorithm called Minimum Risk Increase (MRI) with Risk Increase Threshold (RITH). The proposed MRI with RITH VM placement algorithm selects the host that leads to minimum risk increase to the overall security risk while maintaining the risk increase for each VM does not exceed the value of the proposed RITH constraint; which is set according to the aims of the cloud provider. Simulation results show that using our approach with RITH 0.8 results in security improvement, overall risk was decreased by 2% to 5%, without negative impact on energy consumption or QoS. Moreover, using our approach with RITH less than 0.8 enables the tradeoff between energy consumption and the overall security risk. The maximum overall risk decrease ranged from 10% up to 40%, according to the intensive of the communication overhead between the VMs, while the used energy in its maximum was less than half if we used a non-power-ware VM allocation policy.

云使用的爆炸性增长带来了一些挑战，尤其是云数据中心 (CDC) 的高能耗、由于与同一物理机 (PM) 上的其他风险 VM 共同驻留而给虚拟机 (VM) 带来的新安全风险，以及由于共享资源而导致的服务质量 (QoS) 下降。许多最近的研究提出了动态 VM 合并 (DVMC) 以在 QoS 的最小降级的情况下节省能源。但是，由于缺乏可靠的安全措施，以及在不了解其安全风险程度的情况下整合虚拟机，可能会增加CDC的整体安全风险。为了应对这些挑战，本研究提出了一种安全感知 DVMC (SDVMC)，它由一个安全监控模块 (SMM) 和一个 SDVMC 模块组成。SMM 采用三维安全评估模型，而在 SDVMC 模块中，我们提出了一种新的 VM 放置算法，称为具有风险增加阈值 (RITH) 的最小风险增加 (MRI)。建议的 MRI with RITH VM 放置算法选择导致整体安全风险最小风险增加的主机，同时保持每个 VM 的风险增加不超过建议的 RITH 约束值；这是根据云提供商的目标设置的。仿真结果表明，使用我们的 RITH 0.8 方法可以提高安全性，整体风险降低 2% 到 5%，而对能耗或 QoS 没有负面影响。此外，使用我们的 RITH 小于 0.8 的方法可以在能源消耗和整体安全风险之间进行权衡。最大的整体风险降低范围从 10% 到 40%，