标题：Energy-Aware VM Placement with Periodical Dynamic Demands in Cloud Datacenters
作者：Zhang, Qian ;Wang, Hua ;Zhu, Fangjin ;Yi, Shanwen ;Feng, Kang ;Zhai, Linbo
作者机构：[Zhang, Qian ;Wang, Hua ;Zhu, Fangjin ;Yi, Shanwen ;Feng, Kang ;Zhai, Linbo ] School of Computer Science and Technology, Shandong University, Jinan; 2 更多
会议名称：19th IEEE Intl Conference on High Performance Computing and Communications, 15th IEEE Intl Conference on Smart City, and 3rd IEEE Intl Conference on Data Science and Systems, HPCC/SmartCity/DSS 2017
会议日期：18 December 2017 through 20 December 2017
来源：Proceedings - 2017 IEEE 19th Intl Conference on High Performance Computing and Communications, HPCC 2017, 2017 IEEE 15th Intl Conference on Smart City, SmartCity 2017 and 2017 IEEE 3rd Intl Conference on Data Science and Systems, DSS 2017
摘要：In cloud datacenters, energy-efficient Virtual Machine Placement (VMP) mechanism is needed to maximize energy efficiency. Existing virtual machine (VM) allocation strategies based on whether the VMs' resource demands are assumed to be static or dynamic. Apparently, the former fails to fully utilize resources while the latter, which is implemented on shorter timescales, is either complicated or inefficient. Moreover, most prior VMP algorithms place VMs one by one, which lacks an optimization space. To handle these problems, we predict Gaussian distribution patterns of VM demands and propose an ant-colony-system VM placement algorithm (GACO-VMP) which synchronously coordinates the VMs with complementary resource requirements on the same server. The Gaussian distribution pattern is derived from the VMs running the same job. This mechanism minimizes energy consumption, while guaranteeing high resource utilization and also balancing resource utilization across multiple resources. In addition, we design two new metrics, called cumulative utilization ratio(CUR) and resource balance distance (RBD), in order to measure the overall resource utilization level and the equilibrium of multi-dimensional resource utilization, respectively. Simulations based on Google Cluster real trace indicate that GACO-VMP can achieve remarkable performance gains over two existing strategies in energy efficiency, VM migrations, resource utilization and resource balance. © 2017 IEEE.