Fog Computing Architecture for an IoT enabled smart parking system

In recent years, the benefits of cloud computing have placed it at the heart of the architectures proposed for the Internet of Things (IoT). The homogeneous, predictable, and efficient infrastructure has made Cloud an adequate solution for the processing and analysis of data from IoT objects. However, the benefits of using cloud proved to be problematic for latency sensitive IoT systems that require geographic distribution, consideration of the local environment, and mobility of objects. Fog computing is an emergent concept aimed at extending cloud at the edge of the IoT. Thus, it envisions a layer of nodes (Fogs), making it possible to provide connected objects with support for communication management and data persistence. This paper is motivated by the promising opportunities for the concept of fog computing. We propose a fog computing Framework based on SSN ontology for IoT applications, by applying it to an intelligent parking system that, on the one hand, exploits IoT objects with services and, on the other hand, increases the representation and data consumption with local analyzes at the Fog nodes. For demonstrating, the effectiveness of our implemented framework, simulations have been performed in SUMO, a simulation tool used for urban traffic. Simulation results exhibit that the proposed fog-based implementation reduces the parameters of latency and network usage when contrasted with cloud-based deployment of the smart car parking system.