Managing nonuniformities and uncertainties in vehicle-oriented sensor data over next generation networks
| Autor: | Stavros Nousiasl, Aris S. Lalosl, Dimitris uitzasl, Dimitrios Amaxilatis, Christos Tseliosl, Ioannis Chatzigiannakis, Pablo Mejuto, Samantha Jamson, Olivier Orfila, Orestis Akrivopoulos, Konstantinos Moustakasl |
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| Přispěvatelé: | University of Patras [Patras], Laboratoire sur les Interactions Véhicules-Infrastructure-Conducteurs (IFSTTAR/COSYS/LIVIC), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), University of Leeds, Centre Technologique de l'Automobile de Galice, parent, Spark Works ITC Ltd, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science Real-time computing Cloud computing 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Margin (machine learning) Next-generation network 0202 electrical engineering electronic engineering information engineering Laplacian Matrix Completion [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] 0101 mathematics Edge computing business.industry GRAPH MATRIX COMPLETION MEC Computer Science Applications1707 Computer Vision and Pattern Recognition 020206 networking & telecommunications Root cause Sensor Data V2X 1707 Transmission (telecommunications) SENSOR DATA business 5G Agile software development |
| Zdroj: | PerCom Workshops2018, IEEE International Conference on Pervasive Computing and Communications Workshops PerCom Workshops2018, IEEE International Conference on Pervasive Computing and Communications Workshops, Mar 2018, ATHENES, France. 6p, ⟨10.1109/PERCOMW.2018.8480342⟩ PerCom Workshops 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) |
| Popis: | PerCom Workshops2018, IEEE International Conference on Pervasive Computing and Communications Workshops, ATHENES, GRECE, 19-/03/2018 - 23/03/2018; 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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