Nousiasl, S, Tseliosl, C, Uitzasl, D et al. (8 more authors) (2018) Managing nonuniformities and uncertainties in vehicle-oriented sensor data over next generation networks. In: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops. PerCom Workshops 2018, 19-23 Mar 2018, Athens, Greece. IEEE , pp. 272-277. ISBN 978-1-5386-3227-7
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.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Graph Matrix Completion, V2X, MEC, Sensor Data |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Funding Information: | Funder Grant number EU - European Union 732068 |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Feb 2019 12:51 |
Last Modified: | 14 Feb 2019 12:51 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/PERCOMW.2018.8480342 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:142519 |