AutoScaleSim: a simulation toolkit for auto-scaling Web applications in clouds

Mohammad S. Aslanpour, Adel N. Toosi, Javid Taheri, Raj Gaire

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)

Abstract

Auto-scaling of Web applications is an extensively investigated issue in cloud computing. To evaluate auto-scaling mechanisms, the cloud community is facing considerable challenges on either real cloud platforms or custom test-beds. Challenges include – but not limited to – deployment impediments, the complexity of setting parameters, and most importantly, the cost of hosting and testing Web applications on a massive scale. Hence, simulation is presently one of the most popular evaluation solutions to overcome these obstacles. Existing simulators, however, fail to provide support for hosting, deploying and subsequently auto-scaling of Web applications. In this paper, we introduce AutoScaleSim, which extends the existing CloudSim simulator, to support auto-scaling of Web applications in cloud environments in a customizable, extendable and scalable manner. Using AutoScaleSim, the cloud community can freely implement/evaluate policies for all four phases of auto-scaling mechanisms, that is, Monitoring, Analysis, Planning and Execution. AutoScaleSim can also be used for evaluating load balancing algorithms similarly. We conducted a set of experiments to validate and carefully evaluate the performance of AutoScaleSim in a real cloud platform, with a wide range of performance metrics.

Original languageEnglish
Article number102245
Number of pages20
JournalSimulation Modelling Practice and Theory
Volume108
DOIs
Publication statusPublished - Apr 2021

Keywords

  • Auto-scaling
  • Cloud computing
  • Elasticity
  • Resource provisioning
  • Simulation
  • Web application

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