Impact of theoretical performance models on the design of fog computing infrastructures

The Fog Computing paradigm is increasingly seen as the most promising solution to support Internet of Things applications and satisfy their requirements in terms of response time and Service Level Agreements. For these applications, fog computing offers the great advantage of reducing the response time thanks to the layer of intermediate nodes able to perform pre-processing, filtering and other computational tasks. However, the design of a fog computing infrastructure opens new issues concerning the allocation of data flows coming from sensors over the fog nodes, and the choice of the number of the fog nodes to be activated. Many studies rely on a simplified assumption based on a M/M/1 theoretical queuing model to determine the optimal solution for the fog infrastructure design, but such simplification may result in a mismatch between predicted and achieved performance of the model. In this paper, we measure the aforementioned discordance in terms of response time and SLA compliance. Furthermore, we explore the impact of non-Poissonian service models and validate our results by means of simulation. Our experiments demonstrate that the use of M/M/1 model could lead to SLA violations. On the other hand, the use of sophisticated models for the estimation of the response time can avoid this problem.