How Elasticity Property Plays an Important Role in the Cloud
Tài liệu tham khảo
Armbrust, 2010, A view of cloud computing, Commun. ACM, 53, 50, 10.1145/1721654.1721672
Mell, 2011
Islam, 2012, How a consumer can measure elasticity for cloud platforms, 85
Herbst, 2013, Elasticity in cloud computing: what it is, and what it is not, 23
Han, 2014, Enabling cost-aware and adaptive elasticity of multi-tier cloud applications, Future Gener. Comput. Syst., 32, 82, 10.1016/j.future.2012.05.018
Li, 2011, A scalable and elastic publish/subscribe service, 1254
Garg, 2013, A framework for ranking of cloud computing services, Future Gener. Comput. Syst., 29, 1012, 10.1016/j.future.2012.06.006
Perez-Sorrosal, 2011, Elastic SI-Cache: consistent and scalable caching in multi-tier architectures, VLDB J., 20, 841, 10.1007/s00778-011-0228-8
Schouten
Brebner, 2012, Is your cloud elastic enough?: performance modelling the elasticity of infrastructure as a service (IaaS) cloud applications, 263
Bai, 2011, Cloud testing tools, 1
Coutinho, 2015, Elasticity in cloud computing: a survey, Ann. Telecommun., 70, 289, 10.1007/s12243-014-0450-7
Galante, 2012, A survey on cloud computing elasticity, 263
Galante, 2013, Are public clouds elastic enough for scientific computing?, 294
Amazon CloudWatch. http://aws.amazon.com/cloudwatch, November 2015.
Vaquero, 2011, Dynamically scaling applications in the cloud, ACM SIGCOMM Comput. Commun. Rev., 41, 45, 10.1145/1925861.1925869
Amazon Web Services. http://aws.amazon.com, November 2015.
Microsoft Azure. https://azure.microsoft.com, November 2015.
Google Cloud Platform. https://cloud.google.com, November 2015.
Breitgand, 2005, Automated and adaptive threshold setting: enabling technology for autonomy and self-management, 204
Meng, 2010, Tide: achieving self-scaling in virtualized datacenter management middleware, 17
Marshall, 2010, Elastic site: using clouds to elastically extend site resources, 43
Calheiros, 2012, The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid clouds, Future Gener. Comput. Syst., 28, 861, 10.1016/j.future.2011.07.005
Moore, 2013, A coordinated reactive and predictive approach to cloud elasticity, Cloud Comput., 2013, 87
Nguyen, 2013, Agile: elastic distributed resource scaling for infrastructure-as-a-service
Akansu, 2001
Sharma, 2011, A cost-aware elasticity provisioning system for the cloud, 559
Ali-Eldin, 2012, An adaptive hybrid elasticity controller for cloud infrastructures, 204
Iqbal, 2011, Adaptive resource provisioning for read intensive multi-tier applications in the cloud, Future Gener. Comput. Syst., 27, 871, 10.1016/j.future.2010.10.016
VMware vSphere. https://www.vmware.com/products/vsphere/features/vmotion, November 2015.
Amazon EC2 Auto-scaling. https://aws.amazon.com/autoscaling, November 2015.
Microsoft Azure Service Offerings. https://azure.microsoft.com/en-us/documentation/articles/fundamentals-application-models, November 2015.
Microsoft Azure Auto-scaling. https://azure.microsoft.com/en-us/documentation/articles/cloud-services-how-to-scale, November 2015.
AzureWatch. https://www.paraleap.com/AzureWatch, November 2015.
CloudMonix. http://cloudmonix.com, November 2015.
Google Cloud Platform Instance Group. https://cloud.google.com/compute/docs/instance-groups, November 2015.
VMware. http://www.vmware.com, November 2015.
IBM Cloud. http://www.ibm.com/cloud-computing, November 2015.
Rackspace Cloud. http://www.rackspace.com/cloud, November 2015.
RightScale. http://www.rightscale.com, November 2015.
Scalr. http://www.scalr.com, November 2015.
GoGrid. https://www.datapipe.com/gogrid, November 2015.
Dillon, 2010, Cloud computing: issues and challenges, 27
The Cloud Computing Interoperability Forum. http://www.cloudforum.org, November 2015.
Guide for Cloud Portability and Interoperability Profiles. http://standards.ieee.org/develop/project/2301.html, November 2015.
Agmon Ben-Yehuda, 2012, The resource-as-a-service (RaaS) cloud, 12
Mao, 2012, A performance study on the VM startup time in the cloud, 423
Halting Problem. http://en.wikipedia.org/wiki/Halting_problem, November 2015.
Copil, 2013, SYBL: an extensible language for controlling elasticity in cloud applications, 112
Lorido-Botran, 2014, A review of auto-scaling techniques for elastic applications in cloud environments, J. Grid Comput., 12, 559, 10.1007/s10723-014-9314-7
Buyya, 2010, Intercloud: utility-oriented federation of cloud computing environments for scaling of application services, 13
Pawluk, 2012, Introducing STRATOS: a cloud broker service, 891
Kelly, 2007, A cloudbook for the cloud, Luettu, 24, 30
The Aeolus Project. http://www.aeolus-project.org, November 2015.
Are Long VM Instance Spin-Up Times in the Cloud Costing You Money? http://highscalability.com/blog/2011/3/17/are-long-vm-instance-spin-up-times-in-the-cloud-costing-you.html, November 2015.
Why does Azure Deployment Take so Long? http://stackoverflow.com/questions/5080445/why-does-azure-deployment-take-so-long, November 2015.
Ostermann, 2010, A performance analysis of EC2 cloud computing services for scientific computing, 115
Hill, 2010, Early observations on the performance of Windows Azure, 367
Amazon Spot Instances. http://aws.amazon.com/ec2/spot-instances, November 2015.
Wu, 2012, Jump-start cloud: efficient deployment framework for large-scale cloud applications, Concurr. Comput. Pract. Exper., 24, 2120, 10.1002/cpe.1847
Zhu, 2011, Twinkle: a fast resource provisioning mechanism for internet services, 802
Tang, 2011, FVD: a high-performance virtual machine image format for cloud
Peng, 2012, VDN: virtual machine image distribution network for cloud data centers, 181
Villegas, 2012, Cloud federation in a layered service model, J. Comput. Syst. Sci., 78, 1330, 10.1016/j.jcss.2011.12.017
Kivity, 2014, OSv—optimizing the operating system for virtual machines, vol. 1, 61
Yi, 2010, Reducing costs of spot instances via checkpointing in the Amazon elastic compute cloud, 236
Wee, 2011, Debunking real-time pricing in cloud computing, 585
Chohan, 2010, See spot run: using spot instances for mapreduce workflows, 7
Mattess, 2010, Managing peak loads by leasing cloud infrastructure services from a spot market, 180
Andrzejak, 2010, Decision model for cloud computing under SLA constraints, 257
Yu, 2012, Intelligent database placement in cloud environment, 544
Hong, 2011, Dynamic server provisioning to minimize cost in an IaaS cloud, 147
Chaisiri, 2011, Cost minimization for provisioning virtual servers in Amazon elastic compute cloud, 85
Sohn, 1998, Optimizing computing costs using divisible load analysis, IEEE Trans. Para. Distrib. Syst., 9, 225, 10.1109/71.674315
Chaisiri, 2010, Robust cloud resource provisioning for cloud computing environments, 1
Chaisiri, 2009, Optimal virtual machine placement across multiple cloud providers, 103
Gong, 2010, Press: predictive elastic resource scaling for cloud systems, 9
Shen, 2011, Cloudscale: elastic resource scaling for multi-tenant cloud systems, 5
LaCurts, 2014, Cicada: introducing predictive guarantees for cloud networks
Shen, 2000, Predictive models for proactive network management: application to a production web server, 833
Chandra, 2003, Dynamic resource allocation for shared data centers using online measurements, 381
Gmach, 2007, Capacity management and demand prediction for next generation data centers, 43
Vasić, 2012, Dejavu: accelerating resource allocation in virtualized environments, vol. 40, 423
Dutta, 2012, SmartScale: automatic application scaling in enterprise clouds, 221
Fang, 2012, RPPS: a novel resource prediction and provisioning scheme in cloud data center, 609
Huang, 2012, Resource prediction based on double exponential smoothing in cloud computing, 2056
Islam, 2012, Empirical prediction models for adaptive resource provisioning in the cloud, Future Gener. Comput. Syst., 28, 155, 10.1016/j.future.2011.05.027
Prodan, 2009, Prediction-based real-time resource provisioning for massively multiplayer online games, Future Gener. Comput. Syst., 25, 785, 10.1016/j.future.2008.11.002
Nikravesh, 2015, Towards an autonomic auto-scaling prediction system for cloud resource provisioning, 35
Bodık, 2009, Statistical machine learning makes automatic control practical for internet datacenters, 12
Dawoud, 2011, Elastic VM for cloud resources provisioning optimization, 431
Roy, 2011, Efficient autoscaling in the cloud using predictive models for workload forecasting, 500
Parekh, 2002, Using control theory to achieve service level objectives in performance management, Real-Time Syst., 23, 127, 10.1023/A:1015350520175
Padala, 2007, Adaptive control of virtualized resources in utility computing environments, vol. 41, 289
Kalyvianaki, 2009, Self-adaptive and self-configured CPU resource provisioning for virtualized servers using Kalman filters, 117
Padala, 2009, Automated control of multiple virtualized resources, 13
Park, 2009, Self-tuning virtual machines for predictable escience, 356
Wang, 2011, Fuzzy modeling based resource management for virtualized database systems, 32
Ali-Eldin, 2012, Efficient provisioning of bursty scientific workloads on the cloud using adaptive elasticity control, 31
Chen, 2015, A dynamic resource scheduling method based on fuzzy control theory in cloud environment, J. Control Sci. Eng., 2015, 34, 10.1155/2015/383209
Calheiros, 2011, Virtual machine provisioning based on analytical performance and QoS in cloud computing environments, 295
Villela, 2004, Provisioning servers in the application tier for e-commerce systems, 57
Urgaonkar, 2005, An analytical model for multi-tier internet services and its applications, vol. 33, 291
Urgaonkar, 2008, Agile dynamic provisioning of multi-tier internet applications, ACM Trans. Auton. Adap. Syst. (TAAS), 3, 1, 10.1145/1342171.1342172
Zhang, 2007, A regression-based analytic model for dynamic resource provisioning of multi-tier applications, 27
Bacigalupo, 2010, Resource management of enterprise cloud systems using layered queuing and historical performance models, 1
Kaur, 2014, A resource elasticity framework for QoS-aware execution of cloud applications, Future Gener. Comput. Syst., 37, 14, 10.1016/j.future.2014.02.018
Vilaplana, 2014, A queuing theory model for cloud computing, J. Supercomput., 69, 492, 10.1007/s11227-014-1177-y
Yin, 2014, System resource utilization analysis and prediction for cloud based applications under bursty workloads, Inform. Sci., 279, 338, 10.1016/j.ins.2014.03.123
Su, 2015, SLA-aware tenant placement and dynamic resource provision in SaaS, 615
Li, 2015, Cost-efficient coordinated scheduling for leasing cloud resources on hybrid workloads, Parallel Comput., 44, 1, 10.1016/j.parco.2015.02.003
Liu, 2015, A queuing model considering resources sharing for cloud service performance, J. Supercomput., 71, 4042, 10.1007/s11227-015-1503-z