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2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (2018)
Athens, Greece
March 19, 2018 to March 23, 2018
ISBN: 978-1-5386-3228-4
pp: 272-277
Stavros Nousiasl , University of Patras, Greece
Christos Tseliosl , University of Patras, Greece
Dimitris uitzasl , University of Patras, Greece
Olivier Orfila , IFSTTAR, France
Samantha Jamson , University of Leeds, UK
Pablo Mejuto , CTAG, Spain
Dimitrios Amaxilatis , Spark Works ITC Ltd, UK
Orestis Akrivopoulos , Spark Works ITC Ltd, UK
Ioannis Chatzigiannakis , Sapienza University of Rome, Italy
Aris S. Lalosl , University of Patras, Greece
Konstantinos Moustakasl , University of Patras, Greece
ABSTRACT
Detailed and accurate vehicle-oriented sensor data is considered fundamental for efficient vehicle-to-everything V2X communication applications, especially in the upcoming highly heterogeneous, brisk and agile 5G networking era. Information retrieval, transfer and manipulation in real-time offers a small margin for erratic behavior, regardless of its root cause. This paper presents a method for managing nonuniformities and uncertainties found on datasets, based on an elaborate Matrix Completion technique, with superior performance in three distinct cases of vehicle-related sensor data, collected under real driving conditions. Our approach appears capable of handling sensing and communication irregularities, minimizing at the same time the storage and transmission requirements of Multi-access Edge Computing applications.
INDEX TERMS
Smart cities, Cloud computing, Sensors, Edge computing, Automobiles, Laplace equations, Conferences
CITATION

S. Nousiasl et al., "Managing nonuniformities and uncertainties in vehicle-oriented sensor data over next generation networks," 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)(PERCOM WORKSHOPS), Athens, Greece, 2018, pp. 272-277.
doi:10.1109/PERCOMW.2018.8480342
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