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Smart city article details

Title A Sdn-Based Fine-Grained Measurement And Modeling Approach To Vehicular Communication Network Traffic
ID_Doc 4440
Authors Huo L.; Jiang D.; Zhu X.; Wang Y.; Lv Z.; Singh S.
Year 2022
Published International Journal of Communication Systems, 35, 12
DOI http://dx.doi.org/10.1002/dac.4092
Abstract In smart cities, a large number of vehicles are connected into an intelligent transportation system and share information via the vehicular communication network (VCN). Accurate, fine-grained, and comprehensive traffic measurements are very crucial for the controller's decision making in software-defined networking (SDN) in VCN. Fine-grained traffic measurements can accurately portray network behaviors for VCN. However, this will increase a large amount of measurement overhead. Therefore, how to effectively obtain accurate and fine-grained traffic is a huge challenge for VCN. To the end, this paper proposes a novel accurate and SDN-based fine-grained traffic measurement approach to obtain comprehensive traffic in VCN. Firstly, based on SDN architecture, we exploit the pull-based sampling mechanism to quickly obtain coarse-grained traffic measurement values. Secondly, based on the matrix completion theory, we use both interpolation and optimization methods to obtain fine-grained traffic measurements. Thirdly, the optimization model and detailed algorithm are proposed to attain accurate traffic. Finally, we conduct a larger number of simulations to validate the measurement approach proposed in this paper. Simulation results show that our approach exhibits better performance and is promising. © 2019 John Wiley & Sons, Ltd.
Author Keywords a vehicular communication network; flow sampling; network measurement; software-defined networking; traffic matrix


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