Smart Collection of Real-Time Vehicular Mobility Traces

Nisrine Ibadah, Khalid Minaoui, Mohammed Rziza, Mohammed Oumsis and César Benavente-Peces
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Nisrine Ibadah: LRIT Laboratory, Associated Unit to CNRST (URAC 29), Rabat IT Center, Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014 RP, Morocco
Khalid Minaoui: LRIT Laboratory, Associated Unit to CNRST (URAC 29), Rabat IT Center, Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014 RP, Morocco
Mohammed Rziza: LRIT Laboratory, Associated Unit to CNRST (URAC 29), Rabat IT Center, Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014 RP, Morocco
Mohammed Oumsis: LRIT Laboratory, Associated Unit to CNRST (URAC 29), Rabat IT Center, Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014 RP, Morocco
César Benavente-Peces: ETS Ingeniería y Sistemas de Telecomunicación, Universidad Politécnica de Madria, Ctra Valencia, km 7, 28031 Madrid, Spain

Future Internet, 2018, vol. 10, issue 8, 1-18

Abstract: Mobility trace techniques makes possible drawing the behaviors of real-life movement which shape wireless networks mobility whereabouts. In our investigation, several trace mobility models have been collected after the devices’ deployment. The main issue of this classical procedure is that it produces uncompleted records due to several unpredictable problems occurring during the deployment phase. In this paper, we propose a new procedure aimed at collecting traces while deployment phase failures are avoided, which improves the reliability of data. The introduced procedure makes possible the complete generation of traces with a minimum amount of damage without the need to recover mobile devices or lose them, as it is the case in previous mobility traces techniques. Based on detecting and correcting all accidental issues in real time, the proposed trace scanning offers a set of relevant information about the vehicle status which was collected during seven months. Furthermore, the proposed procedure could be applied to generate vehicular traces. Likewise, it is suitable to record/generate human and animal traces. The research outcomes demonstrate the effectiveness and robustness of the smart collection algorithm based on the proposed trace mobility model.

Keywords: vehicular trace; mobility traces; Morocco traces; tracking; GPS geolocalization; real-time (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2018
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