PAFFI: Performance Analysis Framework for Fog Infrastructures in realistic scenarios

The growing popularity of applications involving the process of a huge amount of data and requiring high scalability and low latency represents the main driver for the success of the fog computing paradigm. A set of fog nodes close to the network edge and hosting functions such as data aggregation, filtering or latency sensitive applications can avoid the risk of high latency due to geographic data transfer and network links congestion that hinder the viability of the traditional cloud computing paradigm for a class of applications including support for smart cities services or autonomous driving. However, the design of fog infrastructures requires novel techniques for system modeling and performance evaluation able to capture a realistic scenario starting from the geographic location of the infrastructure elements. In this paper we propose PAFFI, a framework for the performance analysis of fog infrastructures in realistic scenarios. We describe the main features of the framework and its capability to automatically generate realistic fog topologies, with an optimized mapping between sensors, fog nodes and cloud data centers, whose performance can be evaluated by means of simulation.