Low-Latency Robust Computing Vehicular Networks

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)2130-2144
Journal / PublicationIEEE Transactions on Vehicular Technology
Issue number2
Online published4 Oct 2022
Publication statusPublished - Feb 2023



In this paper, we propose vehicle-centric networking concept to provide low latency services by designing time compression mechanism for computing programs so that the program execution latency can be significantly reduced. In addition, by jointly tailoring data and control planes we implement a highly responsive and cost-efficient edge service. By leveraging network functions virtualization (NFV) and software defined networking (SDN) technologies we provide a suitable environment for at-edge programmability to customize network functionalities for low latency services in multi-platooning systems for vehicular networks. We develop a responsive edge system by implementing control plane over pre-established access points (e.g., road-side units), allocating redundant resources, and utilizing an adaptive service migration mechanism in order to avoid any degradation of the quality of edge services. We design a robust double Knapsack (RDK) framework, where a spare knapsack of redundant resources is allocated to each plane to cope with the uncertainties of vehicle-provided resources. By combining with VNFs, SDN technology has been used to design a centralized management framework to control and monitor the edge computing in multi-platooning systems.

Research Area(s)

  • Dynamic scheduling, Edge computing, low latency, Low latency communication, multi-platooning, Reliability, Security, Software defined networking, Uncertainty, Vehicle dynamics, vehicle-centric networks

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. Related Research Unit(s) information for this record is supplemented by the author(s) concerned.

Citation Format(s)

Low-Latency Robust Computing Vehicular Networks. / Shafigh, Alireza Shams; Lorenzo, Beatriz; Glisic, Savo et al.
In: IEEE Transactions on Vehicular Technology, Vol. 72, No. 2, 02.2023, p. 2130-2144.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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