Rewriting for Efficient Multiformalism Performance Modeling of a Smart City Edge Server

Performance modeling of reconfigurable architectures may challenge well established methods, such as Petri nets and queuing networks: this may limit their applicability and the consequent advantages. These issues may be mitigated by adopting a rewriting approach, in which the model complexity is reduced by adapting the model whenever a reconfiguration occurs in the system. In this paper, we apply a multiformalism modeling approach based on rewriting to the performance evaluation of a reconfigurable and scalable edge server that monitors a portion of a smart city, a crucial subsystem from a national, EU funded research project (This research has been partially funded by MUR PRIN PNRR 2022 PaB-PIF research project, grant number P20227W8ZC, and by Shift2SDV, GA 101194245 - NextGenerationEU - ChipsJU 2024 1-IA-Topic 3 - MIMIT DM 16/12/2022 N. 186485 PNRR M4C2I2.2). The proposed case study shows the effectiveness of the approach.