Power and QoS Aware Multi-level Resource Coordination and Scheduling in Virtualized Servers

Congfeng Jiang, Jingling Mao, Dongyang Ou, Yumei Wang, Xindong You, Jilin Zhang, Jian Wan
2016 International Journal of Grid and Distributed Computing  
Modern cloud data centers are virtualized for resource multiplexing and services consolidations. Virtual machines (VMs) residing in the same server cluster share the same hardware resources and power supply while they may have different QoS requirements for their services and applications. Moreover, the power consumption of the server cluster is highly dynamic since different virtual machines have different workloads due to different services requests. Cluster level power and QoS coordination
more » ... crucial for data center level energy efficiency coordination as well as high quality service provisioning. In this paper we propose the power and QoS aware multi-level resource coordination and scheduling in virtualized servers, i.e., the cluster-level power control layer, the VMs resource allocation layer, and the QoS optimization layer. This three-level controlling framework schedules and allocates hardware resource for QoS guarantee and cluster level power management. We use dynamic frequency scaling for QoS mitigating when power budget changes. The experiment results show that the proposed multi-level coordinated control architecture consumes 5.36% and 6.96% less power for web servers and computing intensive virtual machines, respectively while it can guarantee the response time of web server and execution time of computing tasks no more than those without the proposed controlling approach. He is with the Key Laboratory of Complex Systems Modeling and Simulation, Ministry of Education, China, and the Grid and Services Computing Lab and the Cloud Technology Research Center. His current research interests include big data processing, information retrieval, document recognition and analysis. He is the founded co-chair of international workshop on high performance data intensive computing (HPDIC) and international workshop on performance aspects of cloud and service virtualization (CloudPerf). He is the guest editor of some international journals, including Elsevier Future Generation Computing Systems, Springer Information System Frontiers, and Springer Cluster Computing. Jingling Mao is a master student in
doi:10.14257/ijgdc.2016.9.11.27 fatcat:bcrprhh6ffby7cvw72kdyklroq