OMS: Opportunistic mules for short latency data collection in smart cities. (12th November 2019) - Chehbour, Fairouz; Doukha, Zouina; Moussaoui, Samira; Guerroumi, Mohamed
Summary: In smart city scenarios, data collected by sensors are required to be conveyed to central controllers for processing. Thus, efficient data collection mechanisms considering the urban environment characteristics should take place. To that end, the data mules approach is proved to be efficient. However, being applied to urban environment leads to high data delivery latency due to the characteristics of this environment. Motivated by the need to reduce the collection latency of such an approach, we propose to provide each road segment with a data mule to create a process of distributed data collection. Our scheme leverages opportunistic inter‐vehicular communications for assigning the mule role to adequate vehicles. The simulation in realistic mobility settings reveals that our scheme can provide more than 80% of the area of interest with data mules in less than 1 minute. In addition, the data collection latency can be reduced from 24 hours to few minutes. Abstract : We focus on data gathering from roadside sensors in smart cities (a). We propose a data mule‐based data collection scheme that provides each road of an area of interest (AoI) with a data mule (DM) to create a process of distributed data collection. Our scheme leverages opportunistic inter‐vehicular communications to cover the AoI with a request for DMs election providing each road with adequate DM (b). Simulation results reveal that our scheme can provide more than 80% of the AoI with DMs in less than 1 minute. In addition, the data collection latency can be reduced from 24 hours to few minutes.