부산대학교 도서관

Cloud computing plays an increasingly vital role in both commercial and personal services. In multi-tenant clouds, cloud providers encounter challenges such as physical machine failures and malicious tenant attacks. Ensuring the reliability and robustness of cloud remain significant and complex challenges for cloud providers to improve quality of service and profitability. Previous works either fail to strike a balance between these aspects or result in resource waste and increased costs. In this paper, we propose an innovative virtual machine placement solution without additional resource overhead. Specifically, we place tenants’ virtual machines (VMs) on physical machines (PMs) that meet the reliability requirements specified in the service level agreement, while also limiting the number of PMs to mitigate the impact of malicious attacks, thereby enhancing the robustness of the cloud. However, the dynamic nature of tenant traffic exacerbates the complexity of the problem. To tackle this challenge, we present KR-OPD, a two-stage algorithm with superior competitive ratios. Through large-scale simulations and small-scale testbed, KR-OPD outperforms existing state-of-the-art solutions. For example, our algorithm reduces the affected range of tenants by 47%-64% and the packet loss rate of PM nodes by over 70% compared with other alternatives.