Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers

Concurrency Computation Practice and Experience - Tập 24 Số 13 - Trang 1397-1420 - 2012
Anton Beloglazov1,2, Rajkumar Buyya2
1Anton Beloglazov, CLOUDS Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia.
2Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia

Tóm tắt

SUMMARYThe rapid growth in demand for computational power driven by modern service applications combined with the shift to the Cloud computing model have led to the establishment of large‐scale virtualized data centers. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and switching idle nodes to the sleep mode allows Cloud providers to optimize resource usage and reduce energy consumption. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy‐performance trade‐off, as aggressive consolidation may lead to performance degradation. Because of the variability of workloads experienced by modern applications, the VM placement should be optimized continuously in an online manner. To understand the implications of the online nature of the problem, we conduct a competitive analysis and prove competitive ratios of optimal online deterministic algorithms for the single VM migration and dynamic VM consolidation problems. Furthermore, we propose novel adaptive heuristics for dynamic consolidation of VMs based on an analysis of historical data from the resource usage by VMs. The proposed algorithms significantly reduce energy consumption, while ensuring a high level of adherence to the service level agreement. We validate the high efficiency of the proposed algorithms by extensive simulations using real‐world workload traces from more than a thousand PlanetLab VMs. Copyright © 2011 John Wiley & Sons, Ltd.

Từ khóa


Tài liệu tham khảo

10.1016/j.future.2008.12.001

ASHRAE Technical Committee 99.Datacom equipment power trends and cooling applications 2005.

BeladyC.In the data center power and cooling costs more than the it equipment it supports 2007. URLhttp://www.electronics‐cooling.com/articles/2007/feb/a3/.

10.1109/MC.2007.443

FanX WeberWD BarrosoLA.Power provisioning for a warehouse-sized computer Proceedings of the 34th Annual International Symposium on Computer Architecture (ISCA 2007) ACM New York NY USA 2007;13–23.

de AssunçaoMD GelasJP LefevreL OrgerieAC.The Green Grid’5000: instrumenting and using a Grid with energy sensors Proceedings of the 5th International Workshop on Distributed Cooperative Laboratories: Instrumenting the Grid (INGRID 2010) Poznan Poland 2010.

RanganathanP LeechP IrwinD ChaseJ.Ensemble-level power management for dense blade servers Proceedings of the 33rd International Symposium on Computer Architecture (ISCA 2006) Boston MA USA 2006;66–77.

The green grid consortium 2011. URLhttp://www.thegreengrid.org.

Xen and the art of virtualization Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP 2003) Bolton Landing NY USA.

ClarkC FraserK HandS HansenJG JulE LimpachC PrattI WarfieldA.Live migration of virtual machines Proceedings of the 2nd Symposium on Networked Systems Design and Implementation (NSDI 2005) USENIX Boston MA USA 2005.

10.1007/BF01294260

10.1145/1323293.1294287

10.1007/s10586-008-0070-y

Srikantaiah S, 2009, Energy aware consolidation for cloud computing, Cluster Computing, 12, 1

CardosaM KorupoluM SinghA.Shares and utilities based power consolidation in virtualized server environments Proceedings of the 11th IFIP/IEEE Integrated Network Management (IM 2009) Long Island NY USA 2009.

VermaA AhujaP NeogiA.pMapper: power and migration cost aware application placement in virtualized systems Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware (Middleware 2008) Springer Leuven Belgium 2008;243–264.

VermaA DasguptaG NayakTK DeP KothariR.Server workload analysis for power minimization using consolidation Proceedings of the 2009 USENIX Annual Technical Conference San Diego CA USA 2009;28–28.

GandhiA Harchol-BalterM DasR LefurgyC.Optimal power allocation in server farms Proceedings of the 11th International Joint Conference on Measurement and Modeling of Computer Systems ACM New York NY USA 2009;157–168.

JungG JoshiKR HiltunenMA SchlichtingRD PuC.Generating adaptation policies for multi-tier applications in consolidated server environments Proceedings of the 5th IEEE International Conference on Autonomic Computing (ICAC 2008) Chicago IL USA 2008;23–32.

JungG JoshiKR HiltunenMA SchlichtingRD PuC.A cost-sensitive adaptation engine for server consolidation of multitier applications Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware (Middleware 2009) Urbana Champaign IL USA 2009;1–20.

ZhuX YoungD WatsonBJ WangZ RoliaJ SinghalS McKeeB HyserC GmachD GardnerR et al.1000 islands: integrated capacity and workload management for the next generation data center Proceedings of the 5th International Conference on Autonomic Computing (ICAC 2008) Chicago IL USA 2008;172–181.

10.1016/j.future

KumarS TalwarV KumarV RanganathanP SchwanK.vManage: loosely coupled platform and virtualization management in data centers Proceedings of the 6th international conference on Autonomic computing (ICAC 2009) Barcelona Spain 2009;127–136.

10.1145/277858.277897

10.1007/3-540-45798-4_6

10.1007/s11227-008-0189-x

BerralJL Goiri NouR JuliF GuitartJ GavaldR TorresJ.Towards energy‐aware scheduling in data centers using machine learning Proceedings of the 1st International Conference on energy‐Efficient Computing and Networking Passau Germany 2010;215–224.

Borodin A, 1998, Online Computation and Competitive Analysis

DavidSB BorodinA KarpR TardosG WidgersonA.On the power of randomization in online algorithms Proceedings of the 22nd Annual ACM Symposium on Theory of Computing Baltimore MD USA 1990;379–386.

SongB ErnemannC YahyapourR.Parallel computer workload modeling with Markov chains Proceedings of the 11th International Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP 2005) Cambridge MA USA 2005;47–62.

Minas L, 2009, Energy Efficiency for Information Technology: How to Reduce Power Consumption in Servers and Data Centers

Voorsluys W, 2009, Proceedings of the 1st International Conference on Cloud Computing (CloudCom)

10.1002/0471725250

10.1080/01621459.1979.10481038

Kendall MG, 1973, time‐Series

10.1007/978-3-642-48425-4_2

Cleveland WS, 1993, Visualizing Data

Abdi H, 2007, Encyclopedia of Measurement and Statistics, 648

10.1007/BF02009683

10.1002/spe.995

10.1145/1113361.1113374

10.1145/1508284.1508269

BeloglazovA BuyyaR.Adaptive threshold‐based approach for energy‐efficient consolidation of virtual machines in cloud data centers Proceedings of the 8th International Workshop on Middleware for Grids Clouds and e-Science Bangalore India 2010;4.

Thông tin
Thông tin xuất bản

Concurrency Computation Practice and Experience

Tập 24 Số 13

1397-1420

Thông tin tác giả