Exploiting CloudSim in a multiformalism modeling approach for cloud based systems

Cloud based architectures present many challenges, ranging from poorly dimensioned\r\nhardware to lengthy wait times and resource balancing issues. Most of\r\nthese problems can be mitigated by using proper performance evaluation techniques,\r\ndepending on the accuracy of the model abstracting the real system. The\r\nadoption of a formalism over another to describe the considered infrastructure\r\nplays a crucial role in achieving this goal. In this sense, multiformalism proves\r\nitself to be a powerful modeling approach describing each system component according\r\nto the most suitable representation. This paper presents a novel modeling\r\nmethod oriented to the prediction of cloud architectures performance, suitable for\r\njoining the advantages of high level modeling abstractions and of the detail of\r\na specialized simulator. Generalized Stochastic Petri Nets are used to describe\r\nthe workload and the behavior of users and applications, while Cloudsim, a well\r\nknown cloud infrastructure simulator, is adopted for the cloud part. A case study\r\nof a simplified Edge Computing application is presented to demonstrate the effectiveness\r\nof the proposed approach.