315
Views
0
CrossRef citations to date
0
Altmetric
Articles

Cloud-based software services delivery from the perspective of scalability

ORCID Icon & ORCID Icon
Pages 53-68 | Received 10 Jan 2019, Accepted 08 May 2019, Published online: 15 May 2019

References

  • Liu HH. Software performance and scalability: a quantitative approach. Hoboken (NJ): Wiley; 2009.
  • Atmaca T, Begin T, Brandwajn A, et al. Performance evaluation of cloud computing centers with general arrivals and service. IEEE Trans Parallel Distrib Syst. 2016;27:2341–2348. doi: 10.1109/TPDS.2015.2499749
  • Becker M, Lehrig S, Becker S. Systematically deriving quality metrics for cloud computing systems. Proc. 6th ACM/SPEC Int. Conf. Perform. Eng. New York, NY, USA: ACM; 2015. p. 169–174.
  • Herbst NR, Kounev S, Reussner R. Elasticity in cloud computing: what it is, and what it is not. Proc. 10th Int. Conf. Auton. Comput. ({ICAC} 13) San Jose, CA: USENIX; 2013. p. 23–27.
  • Lehrig S, Eikerling H, Becker S. Scalability, elasticity, and efficiency in cloud computing: a systematic literature review of definitions and metrics. Proceedings of the 11th Int. ACM SIGSOFT Conf. Qual. Softw. Archit. 2015. p. 83–92.
  • Buyya R, Ranjan R, Calheiros RN, et al. Intercloud: utility-oriented federation of cloud computing environments for scaling of application services. In: Hsu C-H, Yang LT, Park JH, editor. Algorithms architecture parallel process. Berlin: Springer; 2010. p. 13–31.
  • Hwang K, Shi Y, Bai X. Scale-out vs. scale-up techniques for cloud performance and productivity. 2014 IEEE 6th Int. Conf. Cloud Comput. Technol Sci. 2014. p. 763–768.
  • AlJahdali H, Albatli A, Garraghan P, et al. Multi-tenancy in cloud computing. 2014 IEEE 8th Int. Symp. Serv. Oriented Syst. Eng. 2014. p. 344–351.
  • Islam S, Lee K, Fekete A, et al. How a consumer can measure elasticity for cloud platforms. Proc. 3rd ACM/SPEC Int. Conf. Perform. Eng. New York, NY, USA: ACM; 2012. p. 85–96.
  • Sharma U, Shenoy P, Sahu S, et al. A cost-aware elasticity provisioning system for the cloud. Proc. 2011 31st Int. Conf. Distrib. Comput. Syst. Washington, DC, USA: IEEE Computer Society; 2011. p. 559–570.
  • Hwang K, Bai X, Shi Y, et al. Cloud performance modeling with benchmark evaluation of elastic scaling strategies. IEEE Trans Parallel Distrib Syst. 2016;27:130–143. doi: 10.1109/TPDS.2015.2398438
  • Blokland K, Mengerink J, Pol M. Testing cloud services: how to test SaaS, PaaS & IaaS. Rocky Nook, Inc.; 2013.
  • Jayasinghe D, Malkowski S, Li J, et al. Variations in performance and scalability: an experimental study in IaaS clouds using multi-tier workloads. IEEE Trans Serv Comput. 2014;7:293–306. doi: 10.1109/TSC.2013.46
  • Jayasinghe D, Malkowski S, Wang Q, et al. Variations in performance and scalability when migrating n-tier applications to different clouds. IEEE 4th Int. Conf. Cloud Comput. 2011.
  • Gao J, Pattabhiraman P, Bai X, et al. SaaS performance and scalability evaluation in clouds. Proc. 2011 IEEE 6th Int. Symp. Serv. Oriented Syst. IEEE; 2011. p. 61–71.
  • Al-Said Ahmad A, Andras P. Measuring the scalability of cloud-based software services. IEEE World Congr. Serv.(SERVICES) San Francisco: IEEE; 2018. p. 5–6. doi: 10.1109/SERVICES.2018.00016
  • Al-Said Ahmad A, Andras P. Measuring and testing the scalability of cloud-based software services. The Fifth IEEE Int. Symp. Innov. Inf. Commun. Technol. (ISIICT 2018). Amman; 2018. p. 1–8. doi: 10.1109/ISIICT.2018.8613297
  • Jennings B, Stadler R. Resource management in clouds: survey and research challenges. J Netw Syst Manag. 2015;23:567–619. doi: 10.1007/s10922-014-9307-7
  • Gao J, Bai X, Tsai WT, et al. SaaS testing on clouds – issues, challenges and needs. 2013 IEEE Seventh Int. Symp. Serv. Syst. Eng. 2013. p. 409–415.
  • Coutinho EF, de Carvalho Sousa FR, Rego PAL, et al. Elasticity in cloud computing: a survey. Ann des Télécommun. 2015;70:289–309. doi: 10.1007/s12243-014-0450-7
  • Hu Y, Deng B, Peng F, et al. A survey on evaluating elasticity of cloud computing platform. In 2016 World Autom. Congr. (WAC) 2016. p. 1–4.
  • Herbst NR, Kounev S, Weber A, et al. BUNGEE: an elasticity benchmark for self-adaptive IaaS cloud environments. 2015 IEEE/ACM 10th Int. Symp. Softw. Eng. Adapt. Self-Managing Syst. 2015. p. 46–56.
  • Bauer A, Herbst N, Kounev S. Design and evaluation of a proactive, application-aware auto-scaler: tutorial paper. Proc. 8th ACM/SPEC Int. Conf. Perform. Eng. New York, NY, USA: ACM; 2017. p. 425–428.
  • Beltran M. Defining an elasticity metric for cloud computing environments. Proc. 9th EAI Int. Conf. Perform. Eval. Methodol. Tools ICST, Brussels, Belgium, Belgium: ICST; 2016. p. 172–179.
  • Kuhlenkamp J, Klems M, Röss O. Benchmarking scalability and elasticity of distributed database systems. Proc VLDB Endow. 2014;7:1219–1230. doi: 10.14778/2732977.2732995
  • Ilyushkin A, Ali-Eldin A, Herbst N, et al. An experimental performance evaluation of autoscaling policies for complex workflows. Proc. 8th ACM/SPEC Int. Conf. Perform. Eng. New York, NY, USA: ACM; 2017. p. 75–86.
  • Jamal MH, Qadeer A, Mahmood W, et al. Virtual machine scalability on multi-core processors based servers for cloud computing workloads. 2009 IEEE Int. Conf. Networking, Archit. Storage. 2009. p. 90–97.
  • Brataas G, Herbst N, Ivansek S, et al. Scalability analysis of cloud software services. 2017 IEEE Int. Conf. Auton. Comput. 2017. p. 285–292.
  • Lehrig S, Sanders R, Brataas G, et al. Cloudstore – towards scalability, elasticity, and efficiency benchmarking and analysis in cloud computing. Futur Gen Comput Syst. 2018;78:115–126. doi: 10.1016/j.future.2017.04.018
  • Saleh I, Nagi K. HadoopMutator: a cloud-based mutation testing framework. In: Schaefer I, Stamelos I, editor. Softw. Reuse Dyn. Syst. cloud beyond. Cham: Springer International; 2014. p. 172–187.
  • Jayathilaka H, Krintz C, Wolski R. Performance monitoring and root cause analysis for cloud-hosted web applications. Proc. 26th Int. Conf. World Wide Web Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee; 2017. p. 469–478.
  • Duan Q. Cloud service performance evaluation: status, challenges, and opportunities – a survey from the system modeling perspective. Dig Commun Netw. 2017;3:101–111. doi: 10.1016/j.dcan.2016.12.002

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.