Elasticity in cloud computing: a survey

  • Emanuel Ferreira CoutinhoEmail author
  • Flávio Rubens de Carvalho Sousa
  • Paulo Antonio Leal Rego
  • Danielo Gonçalves Gomes
  • José Neuman de Souza


Cloud computing is now a well-consolidated paradigm for on-demand services provisioning on a pay-as-you-go model. Elasticity, one of the major benefits required for this computing model, is the ability to add and remove resources “on the fly” to handle the load variation. Although many works in literature have surveyed cloud computing and its features, there is a lack of a detailed analysis about elasticity for the cloud. As an attempt to fill this gap, we propose this survey on cloud computing elasticity based on an adaptation of a classic systematic review. We address different aspects of elasticity, such as definitions, metrics and tools for measuring, evaluation of the elasticity, and existing solutions. Finally, we present some open issues and future directions. To the best of our knowledge, this is the first study on cloud computing elasticity using a systematic review approach.


Cloud computing Elasticity Systematic review Metrics Strategies 



This research is a partial result of the SLA4Cloud project (STIC-AmSud program) supported by CAPES (process: 23038.010147/2013-17). D.G. Gomes and J.N. de Souza would like to thank the support provided by the National Institute of Science and Technology–Medicine Assisted by Scientific Computing (INCT-MACC).


  1. 1.
    Virtualization and containerization of application infrastructure (2014) A comparison, vol. 21. In: University of TwenteGoogle Scholar
  2. 2.
    Aceto G, Botta A, de Donato W, Pescap A (2013) Cloud monitoring: a survey. Comput Netw 0. doi: 10.1016/j.comnet.2013.04.001
  3. 3.
    Aisopos F, Tserpes K, Varvarigou T (2011) Resource management in software as a service using the knapsack problem model. Int J Prod Econ 0. doi: 10.1016/j.ijpe.2011.12.011.
  4. 4.
    Ali-Eldin A, Kihl M, Tordsson J, Elmroth E (2012) Efficient provisioning of bursty scientific workloads on the cloud using adaptive elasticity control. In: Proceedings of the 3rd workshop on Scientific Cloud Computing Date, ScienceCloud ’12. doi: 10.1145/2287036.2287044. ACM, New York, pp 31–40
  5. 5.
    AmazonWebServices: Auto scaling (2013) Online; acessado em setembro-2013.
  6. 6.
    Azure: Microsoft Azure (2013)
  7. 7.
    Bai X, Li M, Chen B, Tsai WT, Gao J (2011) Cloud testing tools. In: Service Oriented System Engineering (SOSE), 2011, pp 1 –12Google Scholar
  8. 8.
    Banzai T, Koizumi H, Kanbayashi R, Imada T, Hanawa T, Sato M (2010) D-cloud: design of a software testing environment for reliable distributed systems using cloud computing technology. In: Cluster, Cloud and Grid Computing (CCGrid),2010 10th IEEE/ACM International Conference on, 631 –636Google Scholar
  9. 9.
    Beloglazov A, Abawajy J, Buyya R (2011) Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Futur Gener Comput Syst:0. doi: 10.1016/j.future.2011.04.017.
  10. 10.
    Bruneo D (2013) A stochastic model to investigate data center performance and QoS in IaaS cloud computing systemsGoogle Scholar
  11. 11.
    Bryant R, Tumanov A, Irzak O, Scannell A, Joshi K, Hiltunen M, Lagar-Cavilla A, de Lara E (2011) Kaleidoscope: cloud micro-elasticity via VM state coloring. In: Proceedings of the sixth conference on Computer systems, EuroSys ’11. doi: 10.1145/1966445.1966471. ACM, New York, pp 273–286
  12. 12.
    Calheiros R, Ranjan R, Buyya R (2011) Virtual machine provisioning based on analytical performance and QoS in cloud computing environments. In: Parallel Processing (ICPP), 2011 International Conference on, pp. 295 –304 , doi: 10.1109/ICPP.2011.17, (to appear in print)
  13. 13.
    Calheiros RN, Toosi AN, Vecchiola C, Buyya R (2012) A coordinator for scaling elastic applications across multiple clouds. Futur Gener Comput Syst 28(8):1350–1362. doi: 10.1016/j.future.2012.03.010. Including Special sections SS: Trusting software behavior and SS: Economics of computing services. CrossRefGoogle Scholar
  14. 14.
    Calheiros RN, Vecchiola C, Karunamoorthy D, Buyya R (2011) The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid clouds. Futur Gener Comput Syst 0. doi: 10.1016/j.future.2011.07.005.
  15. 15.
    Casalicchio E, Silvestri L (2013) Mechanisms for {SLA} provisioning in cloud-based service providers. Comput Netw 57(3):795–810. doi: 10.1016/j.comnet.2012.10.020.
  16. 16.
    Cooper BF, Silberstein A, Tam E, Ramakrishnan R, Sears R (2010) Benchmarking cloud serving systems with YCSB. In: Proceedings of the 1st ACM symposium on Cloud computing, SoCC ’10. doi: 10.1145/1807128.1807152 doi: 10.1145/1807128.1807152. ACM, New York, pp 143–154
  17. 17.
    Copil G, Moldovan D, Truong H L, Dustdar S (2013) Sybl: An extensible language for controlling elasticity in cloud applications. Cluster Computing and the Grid, IEEE International Symposium on 0:112–119.
  18. 18.
    Costa R, Brasileiro F, Lemos G, Mariz D (2011) Sobre a amplitude da elasticidade dos provedores atuais de computao na nuvem, SBRC 2011Google Scholar
  19. 19.
    Cruz F, Maia F, Matos M, Oliveira R, Paulo J a, Pereira J, Vilaça R (2013) Met: workload aware elasticity for nosql. In: Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys ’13. doi: 10.1145/2465351.2465370. ACM, New York, NY, USA, pp 183–196
  20. 20.
    Das S, Agrawal D, El Abbadi A (2013) Elastras: an elastic, scalable, and self-managing transactional database for the cloud. ACM Trans Database Syst 1:5:1–5:45. doi: 10.1145/2445583.2445588 MathSciNetGoogle Scholar
  21. 21.
    Dawoud W, Takouna I, Meinel C (2011) Elastic VM for rapid and optimum virtualized resources’ allocation. In: Systems and Virtualization Management (SVM), 2011 5th International DMTF Academic Alliance Workshop onGoogle Scholar
  22. 22.
    Deng N, Stewart C, Gmach D, Arlitt M, Kelley J (2012) Adaptive green hosting. ACM, New York, USA , pp 135–144Google Scholar
  23. 23.
    Emeakaroha VC, Netto MA, Calheiros RN, Brandic I, Buyya R, Rose CAD (2012) Towards autonomic detection of SLA violations in cloud infrastructures. Futur Gener Comput Syst 28 (7):1017–1029. doi: 10.1016/j.future.2011.08.018. Special section: Quality of service in grid and cloud computing. CrossRefGoogle Scholar
  24. 24.
    Espadas J, Molina A, Jimnez G, Molina M, Ramirez R, Concha D (2011) A tenant-based resource allocation model for scaling software-as-a-service applications over cloud computing infrastructures. Futur Gener Comput Syst:0. doi: 10.1016/j.future.2011.10.013.
  25. 25.
    Etchevers X, Coupaye T, Boyer F, de Palma N, Salaun G (2011) Automated configuration of legacy applications in the cloud. In: Utility and Cloud Computing (UCC), 2011 Fourth IEEE International Conference on, pp. 170 –177 . doi: 10.1109/UCC.2011.32
  26. 26.
    Ferrer AJ, Hernndez F, Tordsson J, Elmroth E, Ali-Eldin A, Zsigri C, Sirvent R, Guitart J, Badia RM, Djemame K, Ziegler W, Dimitrakos T, Nair SK, Kousiouris G, Konstanteli K, Varvarigou T, Hudzia B, Kipp A, Wesner S, Corrales M, Forg N, Sharif T, Sheridan C (2012) Optimis: a holistic approach to cloud service provisioning. Futur Gener Comput Syst 28(1):66–77. doi: 10.1016/j.future.2011.05.022. CrossRefGoogle Scholar
  27. 27.
    Fito J, Goiri I, Guitart J (2010) SLA-driven elastic cloud hosting provider. In: Parallel, Distributed and Network-Based Processing (PDP), 2010 18th Euromicro International Conference on. doi: 10.1109/PDP.2010.16, pp 111 –118
  28. 28.
    Flores H, Srirama SN, Paniagua C (2011) A generic middleware framework for handling process intensive hybrid cloud services from mobiles. In: Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia, MoMM ’11. doi: 10.1145/2095697.2095715. ACM, New York, pp 87–94
  29. 29.
    Galante G, de Bona LCE (2012) A survey on cloud computing elasticity. In: Proceedings of the 5th IEEE/ACM International Conference on Utility and Cloud Computing (UCC ’12)Google Scholar
  30. 30.
    Gao J, Pattabhiraman P, Bai X, Tsai W T (2011) SaaS performance and scalability evaluation in clouds. In: Service Oriented System Engineering (SOSE), 2011 IEEE 6th International Symposium on. doi: 10.1109/SOSE.2011.6139093, pp 61 –71
  31. 31.
    Garg S, Versteeg S, Buyya R (2011) Smicloud: a framework for comparing and ranking cloud services. In: Utility and Cloud Computing (UCC), 2011 Fourth IEEE International Conference on. doi: 10.1109/UCC.2011.36, pp 210–218
  32. 32.
    Garg SK, Versteeg S, Buyya R (2012) A framework for ranking of cloud computing services. Fuur Gener Computt Syst:0. doi: 10.1016/j.future.2012.06.006.
  33. 33.
    Gartner I (2013) Gartner says nearly half of large enterprises will have hybrid cloud deployments by the end of 2017. Online; acessado em outubro-2013.
  34. 34.
    Ghanbari H, Simmons B, Litoiu M, Iszlai G (2011) Exploring alternative approaches to implement an elasticity policy. In: Cloud Computing (CLOUD), 2011 IEEE International Conference on. doi: 10.1109/CLOUD.2011.101, pp 716 –723
  35. 35.
    Ghoshal D, Ramakrishnan L (2012) Frieda: Flexible robust intelligent elastic data management in cloud environments. In: High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:, pp. 1096–1105Google Scholar
  36. 36.
    GoGrid (2012) Cloud hosting, cloud servers, hybrid hosting, cloud infrastructure from gogrid. Online; acessado em janeiro-2012Google Scholar
  37. 37.
    Han R, Ghanem MM, Guo L, Guo Y, Osmond M (2012) Enabling cost-aware and adaptive elasticity of multi-tier cloud applications. Fuur Gener Computt Syst. doi: 10.1016/j.future.2012.05.018,
  38. 38.
    He Q, Zhou S, Kobler B, Duffy D, McGlynn T (2010) Case study for running hpc applications in public clouds. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC ’10. doi: 10.1145/1851476.1851535. ACM, New York, pp 395–401
  39. 39.
    He S, Guo L, Guo Y (2011) Real time elastic cloud management for limited resources, pp 622–629Google Scholar
  40. 40.
    He S, Guo L, Guo Y (2011) Real time elastic cloud management for limited resources, pp 622–629Google Scholar
  41. 41.
    Herbst NR, Kounev S, Reussner R (2013) Elasticity in Cloud Computing: What it is, and What it is Not. USENIX, San Jose CA, pp 23–27Google Scholar
  42. 42.
    Hong YJ, Xue J, Thottethodi M (2012) Selective commitment and selective margin: Techniques to minimize cost in an iaas cloud. In: In: Performance Analysis of Systems and Software (ISPASS), 2012 IEEE International Symposium on. doi: 10.1109/ISPASS.2012.6189210, pp 99–109
  43. 43.
    Islam S, Lee K, Fekete A, Liu A (2012) How a consumer can measure elasticity for cloud platforms. In: In: Proceedings of the third joint WOSP/SIPEW international conference on Performance Engineering, ICPE ’12. doi: 10.1145/2188286.2188301. ACM, New York, USA, pp 85–96
  44. 44.
    Jain R (1991) The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, 1st edn. Wiley, New YorkzbMATHGoogle Scholar
  45. 45.
    Kitchenham B (2004) Procedures for performing systematic reviews. Keele University and NICTA, Tech. rep.Google Scholar
  46. 46.
    Konstanteli K, Cucinotta T, Psychas K, Varvarigou T (2012) Admission control for elastic cloud services. In: Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on. doi: 10.1109/CLOUD.2012.63, pp 41–48
  47. 47.
    Kossmann D, Kraska T, Loesing S (2010) An evaluation of alternative architectures for transaction processing in the cloud. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, SIGMOD ’10. doi: 10.1145/1807167.1807231. ACM, New York, pp 579–590
  48. 48.
    Kousiouris G, Menychtas A, Kyriazis D, Gogouvitis S, Varvarigou T. (2012) Dynamic, behavioral-based estimation of resource provisioning based on high-level application terms in cloud platforms. Fuur Gener Computt Syst:0. doi: 10.1016/j.future.2012.05.009.
  49. 49.
    Krebs R, Momm C, Kounev S (2012) Metrics and techniques for quantifying performance isolation in cloud environments. In: Proceedings of the 8th international ACM SIGSOFT conference on Quality of Software Architectures, QoSA ’12. doi: 10.1145/2304696.2304713. ACM, New York, USA, pp 91–100
  50. 50.
    Kumar D, Shae ZY, Jamjoom H (2012) Scheduling batch and heterogeneous jobs with runtime elasticity in a parallel processing environment. In: Parallel and Distributed Processing Symposium Workshops PhD Forum (IPDPSW), 2012 IEEE 26th International. doi: 10.1109/IPDPSW.2012.10, pp 65–78
  51. 51.
    Li J, Li B, Wo T, Hu C, Huai J, Liu L, Lam K (2012) Cyberguarder: A virtualization security assurance architecture for green cloud computing. Futur Gener Comput Syst 28 (2):379–390. doi: 10.1016/j.future.2011.04.012.
  52. 52.
    Li M, Ye F, Kim M, Chen H, Lei H. (2011) A scalable and elastic publish/subscribe service. In: Parallel Distributed Processing Symposium (IPDPS), 2011 IEEE International. doi: 10.1109/IPDPS.2011.119, pp 1254 –1265
  53. 53.
    Li W, Tordsson J, Elmroth E (2011) Modeling for dynamic cloud scheduling via migration of virtual machines. In: Cloud Computing Technology and Science (CloudCom), 2011 IEEE Third International Conference on. doi: 10.1109/CloudCom.2011.31, pp 163 –171
  54. 54.
    Li X, Qian Z, Chi R, Zhang B, Lu S (2012) Balancing resource utilization for continuous virtual machine requests in clouds. In: Innovative mobile and Internet services in ubiquitous computing. Sixth International Conference on, IMIS, pp 266–273Google Scholar
  55. 55.
    Li Z, O’Brien L, Zhang H, Cai R (2012) On a catalogue of metrics for evaluating commercial cloud services. In: Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing, GRID ’12. doi: 10.1109/Grid.2012.15. IEEE Computer Society, Washington, DC, USA, pp 164–173
  56. 56.
    Li Z, Zhang H, O’Brien L, Cai R, Flint S (2013) On evaluating commercial cloud services: a systematic review. J Syst Softw:0. doi: 10.1016/j.jss.2013.04.021.
  57. 57.
    Lim HC , Babu S, Chase J S , Parekh SS (2009) Automated control in cloud computing: challenges and opportunities. In: Proceedings of the 1st Workshop on Automated Control for Datacenters and Clouds, ACDC ’09. doi: 10.1145/1555271.1555275. ACM, New York, USA, pp 13–18
  58. 58.
    Lorido-Botrán T, Miguel-Alonso J, Lozano JA (2012) Auto-scaling techniques for elastic applications in cloud environments research EHU-KAT-IK. Department of Computer Architecture and Technology, UPV/EHUGoogle Scholar
  59. 59.
    Lu W, Jackson J, Barga R (2010) Azureblast: a case study of developing science applications on the cloud. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC ’10. doi: 10.1145/1851476.1851537. ACM, New York, pp 413–420
  60. 60.
    Lucas-Simarro JL, Moreno-Vozmediano R, Montero RS, Llorente IM (2012) Scheduling strategies for optimal service deployment across multiple clouds. Futur Gener Comput Syst:0. doi: 10.1016/j.future.2012.01.007.
  61. 61.
    Ma R, Lam KT, Wang CL , Zhang C (2010) A stack-on-demand execution model for elastic computing. In: Parallel Processing (ICPP), 2010 39th International Conference on. doi: 10.1109/ICPP.2010.79, pp 208 –217
  62. 62.
    Malik S, Huet F, Caromel D (2012) Racs: A framework for resource aware cloud computing. In: Internet Technology And Secured Transactions, 2012 International Conferece For, pp 680–687Google Scholar
  63. 63.
    Mauch V, Kunze M, Hillenbrand M. (2012) High performance cloud computing. Futur Gener Comput Syst:0. doi: 10.1016/j.future.2012.03.011.
  64. 64.
    Mell P, Grance T (2009) The NIST definition of cloud computing. National Institute of Standards and Technology pp. 53 vol. (6), 50.
  65. 65.
    Menasce DA, Dowdy LW, Almeida VAF (2004) Performance by design: computer capacity planning by example. Prentice Hall PTR, Upper Saddle River, NJ, USAGoogle Scholar
  66. 66.
    Michon E, Gossa J, Genaud S (2012) Free elasticity and free CPU power for scientific workloads on IaaS clouds. In: Parallel and Distributed Systems (ICPADS), 2012 IEEE 18th International Conference on. doi: 10.1109/ICPADS.2012.22, pp 85–92
  67. 67.
    Montero RS, Moreno-Vozmediano R , Llorente IM (2011) An elasticity model for high throughput computing clusters. J Parallel Distrib Comput 71(6):750–757. doi: 10.1016/j.jpdc.2010.05.005. Special Issue on Cloud Computing. CrossRefGoogle Scholar
  68. 68.
    Moreno-Vozmediano R, Montero R, Llorente I (2011) Multicloud deployment of computing clusters for loosely coupled MTC applications Parallel and Distributed Systems. IEEE Trans 22(6):924–930. doi: 10.1109/TPDS.2010.186 Google Scholar
  69. 69.
    Moreno-Vozmediano R, Montero RS, Llorente IM (2009) Elastic management of cluster-based services in the cloud. In: Proceedings of the 1st workshop on Automated control for datacenters and clouds, ACDC ’09. doi: 10.1145/1555271.1555277. ACM, New York, pp 19–24
  70. 70.
    Nie L, Xu Z (2009) An adaptive scheduling mechanism for elastic grid computing, pp 184 –191Google Scholar
  71. 71.
    Niehorster O, Krieger A, Simon J, Brinkmann A (2011) Autonomic resource management with support vector machines. In: Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing, GRID ’11. doi: 10.1109/Grid.2011.28. IEEE Computer Society, Washington, pp 157–164
  72. 72.
    Niu D, Xu H, Li B, Zhao S (2012) Quality-assured cloud bandwidth auto-scaling for video-on-demand applications. In: In: INFOCOM, 2012 Proceedings IEEE. doi: 10.1109/INFCOM.2012.6195785, pp 460 –468
  73. 73.
    Otto J, Stanojevic R, Laoutaris N (2012) Temporal rate limiting: cloud elasticity at a flat fee. In: Computer Communications Workshops (INFOCOM WKSHPS), 2012 IEEE Conference on. doi: 10.1109/INFCOMW.2012.6193478, pp 151 –156
  74. 74.
    Pandey S, Voorsluys W, Niu S, Khandoker A, Buyya R (2012) An autonomic cloud environment for hosting ECG data analysis services. Futur Gener Comput Syst 28(1):147–154. doi: 10.1016/j.future.2011.04.022.
  75. 75.
    Paniagua C, Srirama SN, Flores H (2011) Bakabs: managing load of cloud-based web applications from mobiles. In: Proceedings of the 13th International Conference on Information Integration and web-based applications and services, iiWAS ’11. doi: 10.1145/2095536.2095636. ACM, New York, pp 485–490
  76. 76.
    Pawluk P, Simmons B, Smit M, Litoiu M, Mankovski S (2012) Introducing stratos: A cloud broker service. In: Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on. doi: 10.1109/CLOUD.2012.24, pp 891–898
  77. 77.
    Pawluk P, Simmons B, Smit M, Litoiu M, Mankovski S (2012) Introducing stratos: A cloud broker service. In: Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on. doi: 10.1109/CLOUD.2012.24, pp 891–898
  78. 78.
    Perez-Sorrosal F, Patiño Martinez M, Jimenez-Peris R, Kemme B (2011) Elastic si-cache: consistent and scalable caching in multi-tier architectures. The VLDB Journal 20(6):841–865. doi: 10.1007/s00778-011-0228-8 CrossRefGoogle Scholar
  79. 79.
    Qin X, Wang W, Zhang W, Wei J, Zhao X, Huang T (2012) Elasticat: A load rebalancing framework for cloud-based key-value stores. In: High Performance Computing (HiPC), 2012 19th International Conference on. doi: 10.1109/HiPC.2012.6507481, pp 1–10
  80. 80.
    Raveendran A, Bicer T, Agrawal G (2011) A framework for elastic execution of existing MPI programs. In: Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on. doi: 10.1109/IPDPS.2011.240, pp 940 –947
  81. 81.
    Russell R, Chung M, Balk E (2009) Issues and challenges in conducting systematic reviews to support development of nutrient reference values Tech. rep. Rockville (MD): Agency for Healthcare Research and Quality, USGoogle Scholar
  82. 82.
    S TT, Soares JM, Gomes DG (2011) Cloudreports: Uma ferramenta grfica para a simulao de ambientes computacionaisem nuvem baseada no framework cloudsim. In: IX Workshop em Clouds e Aplicaes - WCGAGoogle Scholar
  83. 83.
    Salah K, Boutaba R (2012) Estimating service response time for elastic cloud applications. In: Cloud Networking (CLOUDNET), 2012 IEEE 1st International Conference on. doi: 10.1109/CloudNet.2012.6483647, pp 12–16
  84. 84.
    Sharma U, Shenoy PJ, Sahu S, Shaikh A (2011) A cost-aware elasticity provisioning system for the cloud. In: International Conference on Distributed Computing Systems (ICDCS) , pp 559–570Google Scholar
  85. 85.
    Shawky DM, Ali AF (2012) Defining a measure of cloud computing elasticity. In: Systems and Computer Science (ICSCS),2012 1st International Conference on. doi: 10.1109/IConSCS.2012.6502449, pp 1–5
  86. 86.
    Sousa FRC, Machado JC (2012) Towards elastic multi-tenant database replication with quality of service. In: Proceedings of the 5th IEEE/ACM International Conference on Utility and Cloud Computing (UCC ’12), pp 168–175Google Scholar
  87. 87.
    Suleiman B, Sakr S, Jeffery DR, Liu A (2012) On understanding the economics and elasticity challenges of deploying business applications on public cloud infrastructure. J. Internet Services and Applications (JISA) 3(2):173–193CrossRefGoogle Scholar
  88. 88.
    Tirado J, Higuero D, Isaila F, Carretero J (2011) Predictive data grouping and placement for cloud-based elastic server infrastructures. In: Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on, pp. 285 –294Google Scholar
  89. 89.
    Toosi A, Calheiros R, Thulasiram R, Buyya R (2011) Resource provisioning policies to increase IaaS provider’s profit in a federated cloud environment. In: High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on. doi: 10.1109/HPCC.2011.44, pp 279–287
  90. 90.
    Tordsson J, Montero RS, Moreno-Vozmediano R, Llorente IM (2012) Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers. Futur Gener Comput Syst 28(2):358–367. doi: 10.1016/j.future.2011.07.003. CrossRefGoogle Scholar
  91. 91.
    Tudoran R, Costan A, Antoniu G, Bougé L (2012) A performance evaluation of azure and nimbus clouds for scientific applications. In: Proceedings of the 2nd International Workshop on Cloud Computing Platforms, CloudCP ’12. doi: 10.1145/2168697.2168701. ACM, New York, pp 4:1–4:6
  92. 92.
    Vaquero LM, Rodero-Merino L, Buyya R (2011) Dynamically scaling applications in the cloud. SIGCOMM Comput Commun Rev 41(1):45–52 . doi: 10.1145/1925861.1925869 CrossRefGoogle Scholar
  93. 93.
    Wee S, Liu H (2010) Client-side load balancer using cloud. ACM, New York, USA , pp 399–405Google Scholar
  94. 94.
    Wong AK, Goscinski AM (2012) A VMD plugin for NAMD simulations on Amazon EC2. Procedia Computer Science 9(0):136–145. doi: 10.1016/j.procs.2012.04.015. Proceedings of the International Conference on Computational Science, ICCS 2012. CrossRefGoogle Scholar
  95. 95.
    Xu H, Li B (2013) A study of pricing for cloud resources. SIGMETRICS Perform. Eval Rev 40(4):3–12. doi: 10.1145/2479942.2479944 CrossRefGoogle Scholar
  96. 96.
    Yu T, Qiu J, Reinwald B, Zhi L, Wang Q, Wang N (2012) Intelligent database placement in cloud environment. In: In: Web Services (ICWS), 2012 IEEE 19th International Conference on, pp 544–551, doi: 10.1109/ICWS.2012.74, (to appear in print)
  97. 97.
    Zhai Y, Liu M, Zhai J, Ma X, Chen W (2011) Cloud versus in-house cluster: evaluating Amazon cluster computer instances for running MPI applications In: State of the Practice Reports, SC ’11. ACM, New York, USA, pp 11:1–11:10Google Scholar
  98. 98.
    Zhao L, Sakr S, Liu A (2013) A framework for consumer-centric SLA management of cloud-hosted databases. IEEE Trans Serv Comput 99:1. . (PrePrints)

Copyright information

© Institut Mines-Télécom and Springer-Verlag France 2014

Authors and Affiliations

  • Emanuel Ferreira Coutinho
    • 1
    Email author
  • Flávio Rubens de Carvalho Sousa
    • 2
  • Paulo Antonio Leal Rego
    • 3
  • Danielo Gonçalves Gomes
    • 4
  • José Neuman de Souza
    • 5
  1. 1.Virtual University Institute (UFC VIRTUAL)Federal University of Ceara (UFC)FortalezaBrazil
  2. 2.Teleinformatics Engineering Department (DETI)Federal University of Ceara (UFC)FortalezaBrazil
  3. 3.Federal University of Ceara (UFC)FortalezaBrazil
  4. 4.Teleinformatics Engineering Department (DETI) Group of Computer Networks, Software Engineering, and Systems (GREat)Federal University of Ceara (UFC)FortalezaBrazil
  5. 5.Computer Science DepartmentFederal University of Ceara (UFC)FortalezaBrazil

Personalised recommendations