Virtual Machine Scheduling Policy Based on Real-time Computing Platform

doi:10.3969/j.issn.1000-3428.2016.05.006

Abstract

Abstract: In cloud computing environment,technologies such as dynamic migration and scaling decrease both violations of Service Level Agreement(SLA) and energy cost.But frequent migration of Virtual Machine(VM) can increase SLA violations and cause the performance degradation.To minimize SLA violations and migrations,this paper proposes a scalable real-time VM scheduling policy.It builds a scalable system with Kafka and Spark to analyze history data,predicates future load and generates migration plan.Simulation experimental result shows that the policy decreases migrations by 50% while maintaining low SLA violation rate compared with native policy of CloudSim.

Key words: cloud computing, real-time computing, Virtual Machine(VM) dynamic migration, dynamic scaling, Service Level Agreement(SLA)

摘要： 在云计算环境中,有效的虚拟机在线迁移和动态扩容技术有助于保障服务等级协议(SLA)的实现,并能够降低能耗成本。但虚拟机的迁移会导致性能下降,频繁迁移会增加SLA违约率。为此,以降低SLA违约率和迁移次数为目标,提出一种可伸缩的实时虚拟机调度策略,利用分布式消息系统Kafka和分布式计算系统Spark构建可扩展系统,基于历史数据预测负载并实时产生调度方案。仿真实验结果表明,与CloudSim原有策略相比,该策略在维持低SLA违约率的同时,迁移次数下降50%左右。

关键词: 云计算, 实时计算, 虚拟机动态迁移, 动态扩容, 服务等级协议

CLC Number:

TP391

WANG Zhiping,LI Xiaoyong. Virtual Machine Scheduling Policy Based on Real-time Computing Platform[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.05.006.

王志平,李小勇. 基于实时计算平台的虚拟机调度策略[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.05.006.

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References

参考文献［1］Armbrust M,Fox A,Griffith R,et al.A View of Cloud Computing［J］.Communications of the ACM,2010,53(4):50-58. ［2］Amazon EC2［EB/OL］.［2015-06-14］.http://aws.amazon.com/cn/ec2/. ［3］Clark C,Fraser K,Hand S,et al.Live Migration of Virtual Machines［C］//Proceedings of the 2nd Conference on Networked Systems Design & Implementation［S.1.］:USENIX Association,2005:273-286. ［4］VMware vSphere 5.0更改CPU热插拔设置［EB/OL］.［2015-06-14］.https://pubs.vmware.com/vsphere-50/index.jsp#com.vmware.vsphere.vm_admin.doc_50/GUID-F102B9BD-1B92-4AC5-ADC0-BE4E90473C5F.html. ［5］VMware vSphere 5.0在vSphere Client中更改内存热添加设置［EB/OL］.［2015-06-14］.https://pubs.vmware.com/vsphere-50/index.jsp?topic=%2Fcom.vmware.vsphere.vm_admin.doc_50%2FGUID-0B4C3128-F854-43B9-9D80-A20C0C8B0FF7.html. ［6］Chen G,He W,Liu J,et al.Energy-aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services［C］//Proceedings of NSDI’08.Washington D.C.,USA:IEEE Press,2008:337-350. ［7］Hyser C,Mckee B,Gardner R,et al.Autonomic Virtual Machine Placement in the Data Center,HPL-2007-189［R］.［ S.l.］:HP Laboratory,2008. ［8］Hermenier F,Lorca X,Menaud J M,et al.Entropy:A Consolidation Manager for Clusters［C］//Proceedings of 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments.New York:ACM Press,2009:41-50. ［9］Nguyen V H,Dang T F,Menaud J M.Autonomic Virtual Resource Management for Service Hosting Platforms［C］//Proceedings of 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing.［S.1.］:IEEE Computer Society,2009:1-8. ［10］Wood T,Shenoy P J,Venkataramani A,et al.Black-box and Gray-box Strategies for Virtual Machine Mig-ration［C］//Proceedings of NSDI’07.Washington D.C.,USA:IEEE Press,2007:11-17. ［11］Piao J T,Yan J.A Network-aware Virtual Machine Placement and Migration Approach in Cloud Computing［C］//Proceedings of the 9th International Conference on Grid and Cooperative Computing.Washington D.C.,USA:IEEE Press,2010:87-92. ［12］Shrivastava V,Zerfos P,Lee K W,et al.Application-aware Virtual Machine Migration in Data Centers［C］//Proceedings of INFOCOM’11.Washington D.C.,USA:IEEE Press,2011:66-70. ［13］Kliazovich D,Bouvry P,Khan S U.DENS:Data Center Energy-efficient Network-aware Scheduling［J］.Cluster Computing,2013,16(1):65-75. ［14］Luo Y,Zhang B,Wang X,et al.Live and Incremental Whole-system Migration of Virtual Machines Using Block-bitmap［C］//Proceedings of 2008 IEEE International Conference on Cluster Computing.Washington D.C.,USA:IEEE Press,2008:99-106. ［15］Buyya R,Beloglazov A,Abawajy J.Energy-efficient Management of Data Center Resources for Cloud Computing:A Vision,Architectural Elements,and Open Challenges［J］.Future Generation Computer Systems,2012,(28):755-768. ［16］Berral J L,Goiri I,Nou R,et al.Towards Energy-aware Scheduling in Data Centers Using Machine Learning［C］//Proceedings of the 1st International Conference on Energy-efficient Computing and Networking.New York,USA:ACM Press,2010:215-224. ［17］Bobroff N,Kochut A,Beaty K.Dynamic Placement of Virtual Machines for Managing Slaviolations［C］//Proceedings of the 10th IFIP/IEEE International Symposium on Integrated Network Management.Washington D.C.,USA:IEEE Press,2007:119-128. (下转第41页) (上接第34页) ［18］Dutta S,Gera S,Verma A,et al.Smartscale:Automatic Application Scaling in Enterprise Clouds［C］//Proceedings of the 5th IEEE International Conference on Cloud Computing.Washington D.C.,USA:IEEE Press,2012:221-228. ［19］Leverich J,Monchiero M,Talwar V,et al.Power Management of Datacenter Workloads Using Percore Power Gating［J］.Computer Architecture Letters,2009,8(2):48-51. ［20］David H,Fallin C,Gorbatov E,et al.Memory Power Mana-gement via Dynamic Voltage/Frequency Scaling［C］//Proceedings of the 8th ACM International Conference on Autonomic Computing.New York,USA:ACM Press,2011:31-40. ［21］Apache Kafka［EB/OL］.［2015-06-14］.http://kafka.apache.org/. ［22］Apache SparkTM-lightning-fast Cluster Computing［EB/OL］.［2015-06-14］.http://spark.apache.org/. ［23］Zaharia M,Das T,Li H,et al.Discretized Streams:An Efficient and Fault-tolerant Model for Stream Processing on Large Clusters［C］//Proceedings of the 4th USENIX Conference on Hot Topics in Cloud Ccomputing.［S.1.］:USENIX Association,2012:10. ［24］Linear Regression［EB/OL］.［2015-06-14］.http://en.wikipedia.org/wiki/Linear_regression. ［25］Category:SLA［EB/OL］.［2015-06-14］.http://www. ovirt.org/Category:SLA. ［26］SLA Definition［EB/OL］.［2015-06-14］.http://docs.giga-spaces.com/xap97/configuring-the-processing-unit-sla.html. ［27］Fan X,Weber W D,Barroso L A.Power Provisioning for a Warehouse-sized Computer［C］//Proceedings of ACM SIGARCH Computer Architecture News.New York:ACM Press,2007,35(2):13-23. ［28］Buyya R,Ranjan R,Calheiros R N.Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit:Challenges and Opportunities［C］//Proceedings of IEEE International Conference on High Performance Computing & Simulation.Washington D.C.,USA:IEEE Press,2009:1-11. ［29］Beloglazov A,Buyya R.Optimal Online Deterministic Algorithms and Adaptive Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in Cloud Data Centers［J］.Concurrency and Computation:Practice and Experience,2012,24(13):1397-1420. 编辑索书志

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