# FOXS-GSC--Fast Offset Xpath Service with HexagonS Communication
## 1 Introduction  
Embedded devices are now available for vehicles, supporting a wide range of services and applications aimed at managing traffic both in urban areas and on roadways [1]. These devices can sense the streets and highways of a city, providing new services and assisting ITS in the aim of optimizing the entire infrastructure of a city's transport system [2]. To illustrate the potential of ITS applications and services, a study conducted by the World Health Organization [3] has revealed that road accidents worldwide cause 1.35 million deaths per year, with an estimated cost to the world economy of USD 1.8 trillion in crash injuries [4]. Frontal collisions account for about 33.7% of these accidents, and about 32.6% are due to lack of attention [5]. Thus, devices and mechanisms that monitor traffic and detect road events can help to reduce such accidents. To monitor traffic on public roads, a mechanism is employed that verifies the density, direction, and other information of the vehicles [6]. This mechanism aims to detect slowtraffic, possible congestion points, and traffic interruptions, enabling drivers to avoid them [7; 8]. The lack or improper implementation of such a traffic monitoring system can significantly impact a nation's budget. For example, traffic congestion costs approximately 2% of the European Union's GDP [9], and over 160 billion US dollars per year in the United States [10]. To address this issue, computational research is necessary to provide the infrastructure needed to cover the entire transport system, which requires developing efficient information and communication technologies that can integrate vehicles [11; 12]. This integration can be accomplished through communication between vehicles as well as between vehicles and roadside infrastructure such as a cellular network. There are various approaches in the literature that aim to detect and alleviate traffic congestion in urban areas through vehicle networks [13; 14]. One such approach, described in [13], employs vehicle-to-vehicle communication to estimate the speed and density of vehicles on the road. While this technique does not rely on infrastructure, it involves several challenges, such as minimizing information redundancy, reducing network overhead, and achieving accurate classification in a short amount of time. Additionally, this approach may suffer from frequent disconnections due to the highly dynamic topology of vehicle networks. Another approach, described in [14], uses communication between vehicles and a roadside access point (known as Vehicle-to-Infrastructure or V2I communication) to estimate their speed, location, and destination. While this technique appears to be more reliable, it faces various communication challenges, such as redundant data and long information delivery time. The fog computing paradigm is employed to overcome these limitations by leveraging the proximity of vehicles to reduce the delay in sending and receiving information. In this sense, the present work proposes a new communication mechanism called Fast Offset Xpath Service with hexaGonS Communication (FOXS-GSC) based on FOXS [15]. Unlike previous works that focused on monitoring and classifying traffic conditions and calculating vehicle routes based on a fog computing infrastructure, FOXS-GSC focuses on developing an efficient communication protocol that allows vehicles far from a cloudlet to receive and send information about their routes. The proposed protocol divides the environment into sectors based on the number of vehicles in them, taking advantage of traffic congestion characteristics, where the density is more significant in congested regions. FOXS-GSC allows greater coverage of the service even when the infrastructure is not within the coverage radius. However, the service may be unreachable due to particular properties of the current network.