A blockchain-based Fog-oriented lightweight framework for smart public vehicular transportation systems

Thar Baker, Muhammad Asim, Hezekiah Samwini, Nauman Shamim, Mohammed M. Alani, Rajkumar Buyya

Research output: Contribution to journalArticle (journal)peer-review

38 Citations (Scopus)

Abstract

Rapid urbanization is putting a strain on the transport systems of cities worldwide. The effects of this trend include prolonged traffic jams and increasing environmental pollution from rising CO 2 emissions. As city planning requires innovative ways of dealing with the rapid urbanization trend, technological solutions were proposed such as cloud computing, smart vehicles, and Vehicular Ad hoc NETwork (VANET). In this paper, we take advantage of next-generation network technologies to propose a responsive and lightweight framework for smart transportation system which employs blockchain for authentication using fog computing's improvement over cloud computing for distributed applications to provide an efficient and secure transportation system. We take into account the future technologies of 5G and Beyond 5G (B5G) and argue that the integration of B5G technologies, federated learning, blockchain, and edge computing provides the perfect platform necessary for a smart transportation system The evaluation of the proposed framework is done by comparing it to the current cloud-based approach in iFogSim, a popular simulation tool for fog computing research. The evaluation of blockchain-based authentication was done using a customized implementation of blockchain executed in an experimental setup. The simulation results showed that the proposed framework provides superior performance in terms of security, latency, and energy consumption of the system.

Original languageEnglish
Article number108676
JournalComputer Networks
Volume203
Issue number108676
Early online date20 Dec 2021
DOIs
Publication statusPublished - 11 Feb 2022

Keywords

  • Beyond 5G technologies
  • Blockchain
  • Federated learning
  • Fog
  • Vehicular clouds
  • Vehicular networks

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