![]() Generally, route suggestion services rely on data from specific regions, as traffic conditions, which may be irrelevant to other regions of a city. These characteristics enable Fog Computing to offer an ideal platform for highly dynamic and heterogeneous ITS environment. Although, the ITS may also leverage mobility to perform data delivery activities to various stakeholders scalability–an ITS needs to be scalable, due to the high number of vehicles and sensors and extensibility–if the city grows, the ITS infrastructure also needs to grow to support the expanded region. ![]() However, the scope of the data gathered is restricted to the location of the sensors that generated such data real-time interaction–re-routing systems have real-time requirements mobility–an ITS is used to optimize the mobility of vehicles in the city. The main benefits to designing an ITS with Fog paradigm are : low latency–some ITS data have strict time constraints, such as data for re-route systems predominant wireless access–modern ITS systems heavily rely on wireless communications wide geographical distribution–ITS has sensors geographically spread. Thus, designing ITS services that have a required quality of service (QoS) is a challenge. Theses characteristics imply in some issues for ITS services requirements such as mobility, frequent network disconnections, networking latency and end-to-end responsiveness time. ITS services and applications have intrinsic characteristics regarding the way they process, store and disseminate a vast amount of data generated in ITS. In this way, vehicles can communicate with other vehicles through vehicle-to-vehicle (V2V) communication and with the network infrastructure (e.g., RSU-Road Side Unit) through vehicle-to-infrastructure (V2I) communication. In ITS, vehicles are equipped with sensors (e.g., GPS and Galileo), processors and wireless communication modules. Moreover, an ITS does not only aim to provide traffic management services (for instance, to prevent traffic jam) but also security management services and infotainment applications to drivers, passengers and pedestrians. An ITS uses communication, processing and sensing technologies to improve the urban traffic and consequently the flow of vehicles in the urban road. One approach to prevent these problems is the development of an Intelligent Transport System (ITS). For instance, the congestion cost in the United States, the United Kingdom and Germany were almost $461 billion in 2017. Among them are the increase in greenhouse gas emissions and many hours stuck in traffic congestions, thus resulting in health issues and monetary losses. One of the most affected sectors is the urban transport systems, in which inefficiencies may lead to many negative consequences. Such uncontrolled urban growth typically causes significant stress on city structures due to the unexpected demand of various resources and services. The unplanned development of urban centers often is associated with severe socio-economic problems. When considering communication evaluation metrics, FOXS reaches a better result than other solutions on the packet collisions metric (up to 11.5%) and on the application delay metric (up to 30%). When compared with related works, FOXS shows a reduction in stop time by up to 70%, the CO 2 emissions by up to 29% and, the planning time index by up to 49%. ![]() In order to validate FOXS, our performance evaluation considers two realistic urban scenarios with different characteristics. Therefore, it is possible to take advantage of the inherent aspects of this paradigm, such as low latency, processing load balancing, scalability, geographical correlation and the reduction of bandwidth usage. Unlike the related works, FOXS is modeled using the Fog computing paradigm. FOXS aims to reduce the problems generated by a traffic jam in a distributed way through roads classification and the suggestion of new routes to vehicles. ![]() In an attempt to solve this problem, this article proposes a traffic service to control congestion, named FOXS–Fast Offset Xpath Service. Frustrations, monetary losses, lost time, high fuel consumption and CO 2 emissions are some of the problems caused by traffic jams in urban centers. ![]()
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