SoLVE: A Localization System Framework for VANets using the Cloud and Fog Computing

Abstract

Usually, vehicles are equipped with Global Positioning System (GPS), which can provide its position estimation. However, GPS can become erroneous or unavailable in cases of some indoor scenarios, such as tunnels and dense urban areas where there is no straight visibility to satellites. In Vehicular Ad Hoc Networks (VANets), some critical applications such as Driverless Vehicles and Blind Crossing require a precise localization system. In this work, we proposed a new localization system framework for VANets using the Cloud and Fog Computing paradigm. Our framework, called SoLVE (acronym of three keywords: System, Localization, and VANets), takes advantage of both Fog Computing and the location awareness of the RoadSide Units (RSUs) and Smart Traffic Lights (STL) in order to provide a precise estimate the position of vehicles within a Fog Network. Fogs can be as many as needed to cover the entire area of the localization system. Some of framework challenges, and implementations are discussed. Also, some use cases are described as well future research directions are highlighted.