Modeling and Simulating Stream Processing Platforms

Stream processing platforms allow processing and analyzing real-time data. Several tools have been developed for these platforms to guarantee that the applications running on them are scalable, fast, and fault-tolerant and that they can be deployed on many processors. However, determining the proper number of processors suitable to hold a given stream processing-based software application is challenging, especially if the application is intended to serve a large user community. In this paper, we propose to model and simulate stream processing platforms for performance evaluation purposes. In our case study, we simulated a commonly used application for the analysis of Twitter streams with Storm. We evaluate its performance under different workloads. Our simulator supports profiling to measure various aspects of the application s performance. Results show that the simulator can replicate the metrics reported by the application running on a real platform with minimal error. © 2023 IEEE.