TY - JOUR
T1 - AutoScaleSim
T2 - a simulation toolkit for auto-scaling Web applications in clouds
AU - Aslanpour, Mohammad S.
AU - Toosi, Adel N.
AU - Taheri, Javid
AU - Gaire, Raj
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Auto-scaling
KW - Cloud computing
KW - Elasticity
KW - Resource provisioning
KW - Simulation
KW - Web application
UR - http://www.scopus.com/inward/record.url?scp=85098704409&partnerID=8YFLogxK
U2 - 10.1016/j.simpat.2020.102245
DO - 10.1016/j.simpat.2020.102245
M3 - Article
AN - SCOPUS:85098704409
VL - 108
JO - Simulation Modelling Practice and Theory
JF - Simulation Modelling Practice and Theory
SN - 1569-190X
M1 - 102245
ER -