Energy Guided and Workload Adaptive Modeling for Live Migration

Abstract:

Live migration provides desirable benefits in the field of energy saving, which packs service into fewer physical servers while maintaining the performance level. In this paper we present energy guided and workload adaptive modeling for live migration, two models are developed respectively including energy guided migration model and workload adaptive model, the former model selects the best migrating virtual machine (VM) candidate with the minimal energy consumption while the later model chooses the best migrated physical server candidate in terms of both energy and workload characteristics, furthermore, concerning the service quality, workload adaptive model also takes charge of the determination of the live migration moment. The experiments results show that our approach achieves significant energy saving and robust live migration.

• Periodical: Advanced Materials Research (Volume 748)
• Pages: 982-986
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.748.982
• Online since: August 2013
• Authors: Bing Wei
• Keywords: Energy Consumption (EC), Live Migration, Modeling, Workload

References

[1] J. Lange, K. Pedretti, T. Hudson, P. Dinda, Z. Cui, L. Xia, P. Bridges: New High Performance Operating Systems for Scalable Virtualized and Native Supercomputing. IPDPS'10, Atlanta, Georgia, USA, April 19-23, 2010, pp.1-12.

DOI: 10.1109/ipdps.2010.5470482

[2] P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho. Xen and the Art of Virtualization. SOSP'03, Lake George, New York, USA, October 19-22, 2003, pp.164-177.

DOI: 10.1145/1165389.945462

[3] K. Sato, H. Sato, S. Matsuoka. Model-based Optimization for Data-intensive Application on Virtual Cluster. Grid'08, Tsukuba, Japan, pp.367-368.

DOI: 10.1109/grid.2008.4662824

[4] T. Wood, P. Shenoy, A. Venkataramani and M. Yousif. Blackbox and Gray-box Strategies for Virtual Machine Migration. NSDI'07, Cambridge, MA, USA, April 11-13, 2007, pp.229-242.

[5] Verma, P. Ahuja, and A. Neogi. pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems. Middleware'08, Verag, Leuven, Belgium, 2008, pp.243-264.

DOI: 10.1007/978-3-540-89856-6_13

[6] M. Y. Lim, F. Rawson, T. Bletsch, and V. W. Freeh. PADD: Power Aware Domain Distribution. ICDCS'09, Montreal, Quebec, Canada, June 22-26, 2009, pp.239-247.

DOI: 10.1109/icdcs.2009.47

[7] M. Cardosa, M. R. Korupolu and A. Singh. Shares and Utilities Based Power Consolidation in Virtualized Server Environments. IM'09, New York, NY, USA, June 1-5, 2009, pp.327-334.

DOI: 10.1109/inm.2009.5188832

[8] L. Hu, H. Jin, X. Liao, and X. Xiong: A Novel Scheduling Policy for Power Reduction in Cluster with Virtual Machines. Cluster'08, 2008, Tsukuba, Japan, pp.13-22.

DOI: 10.1109/clustr.2008.4663751

[9] B. Wei, C. Lin, and X. Z. Kong, "Energy Aware Modeling for live migration", 2011.

[10] H. Liu, C. Z. Xu, H. Jin, J. Gong, and X. Liao, Performance and Energy Modeling for Live Migration of Virtual Machines, In HPDC'11, June 8-11, 2011.

[11] S. Srikantaiah, A. Kansal, and F. Zhao, Energy Aware Consolidation for Cloud Computing, USENIX HotPower'08, 2008.