2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring) 2019
DOI: 10.1109/vtcspring.2019.8746302
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Abstract: Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to b… Show more

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Cited by 15 publications
(8 citation statements)
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“…Random linear network coding (RLNC) [12] achieves the capacity of wireless networks with packet loss for a wide range of scenarios [10]- [14]. Existing works have studied the used of RLNC for vehicle related communications, such as content distribution [40], data offloading [41] and platooning [42].…”
Section: A Challenge and Solutionmentioning
confidence: 99%
“…Random linear network coding (RLNC) [12] achieves the capacity of wireless networks with packet loss for a wide range of scenarios [10]- [14]. Existing works have studied the used of RLNC for vehicle related communications, such as content distribution [40], data offloading [41] and platooning [42].…”
Section: A Challenge and Solutionmentioning
confidence: 99%
“…Our framework provides also tools to investigate the Key Performance Indicators (KPIs) shown in Figs. [3][4][5][6][7][8][9][10]. These figures will be further discussed in the next section.…”
Section: Datamentioning
confidence: 99%
“…StationIDID of the transmitter/receiverGenDeltaTimeThe remainder of T imestamp/65546[6] SeqNum Sequence number of the transmitted/received CAM[7] GpsLonLongitude of the current position of the transmitter/receiver GpsLat Latitude of the current position of the transmitter/receiver CamLon Longitude of the position of the transmitter/receiver as encapsulated in a CAM CamLat Latitude of the position of the transmitter/receiver as encapsulated in a CAM SpeedConf Encoding configuration for the speed [6] VehHeading Heading of the transmitter GpsSpeed Speed of the transmitter/receiver CamSpeed Speed of the transmitter as encapsulated in a CAM Timestamp Timestamp at the moment of creation of a CAM CamLength Byte-length of a CAM RSSI The RSSI value of a received CAM Experimental Design, Materials, and Methods…”
mentioning
confidence: 99%
“…Mining and analysing big medical data, using the valuable information to assist doctors in the diagnosis and treatment of diseases, and improving the efficiency of doctors’ diagnosis have become an urgent problem to be solved. As the support platform for analysis and processing of medical big data, cloud computing provides strong technical support for hospital information construction [7, 8]. In recent years, experts and scholars have proposed a medical big data mining platform and algorithm based on cloud computing.…”
Section: Introductionmentioning
confidence: 99%