An autonomic provisioning framework for outsourcing data center based on virtual appliances

  • Authors:

  • Xiaoying Wang;Zhihui Du;Yinong Chen;Sanli Li;Dongjun Lan;Gang Wang;Ying Chen

  • Affiliations:

  • Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084;Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084;Computer Science & Engineering Department, Arizona State University, Tempe, USA AZ 85287;Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084;IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094

  • Venue:
  • Cluster Computing
  • Year:
  • 2008

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Abstract

As outsourcing data centers emerge to host applications and services from many different organizations, it is critical for data center owners to isolate different applications while dynamically and optimally allocate sharable resources among them. To address this issue, we propose a virtual-appliance-based autonomic resource provisioning framework for large virtualized data centers. We present the architecture of the data center with enriched autonomic features. We define a non-linear constrained optimization model for dynamic resource provisioning and present a novel analytic solution. Key factors, including virtualization overhead and reconfiguration delay, are incorporated into the model. Experimental results based on a prototype demonstrate that the system-level performance has been greatly improved by taking advantage of fine-grained server consolidation, and the whole system exhibits flexible adaptation in failure scenarios. Experiments with the impact of switching delay also show the efficiency of the framework due to significantly reduced provisioning time.