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Open AccessArticle

Exploiting Mobile Edge Computing for Enhancing Vehicular Applications in Smart Cities

College of Information Technology, UAE University, Al Ain 15551, UAE
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Sensors 2019, 19(5), 1073; https://doi.org/10.3390/s19051073
Received: 27 September 2018 / Revised: 20 November 2018 / Accepted: 23 November 2018 / Published: 2 March 2019
Mobile edge computing (MEC) has been recently proposed to bring computing capabilities closer to mobile endpoints, with the aim of providing low latency and real-time access to network information via applications and services. Several attempts have been made to integrate MEC in intelligent transportation systems (ITS), including new architectures, communication frameworks, deployment strategies and applications. In this paper, we explore existing architecture proposals for integrating MEC in vehicular environments, which would allow the evolution of the next generation ITS in smart cities. Moreover, we classify the desired applications into four major categories. We rely on a MEC architecture with three layers to propose a data dissemination protocol, which can be utilized by traffic safety and travel convenience applications in vehicular networks. Furthermore, we provide a simulation-based prototype to evaluate the performance of our protocol. Simulation results show that our proposed protocol can significantly improve the performance of data dissemination in terms of data delivery, communication overhead and delay. In addition, we highlight challenges and open issues to integrate MEC in vehicular networking environments for further research. View Full-Text
Keywords: mobile edge computing (MEC); intelligent transportation systems (ITS); smart cities; vehicular ad hoc networks (VANETs); vehicular edge computing (VEC) mobile edge computing (MEC); intelligent transportation systems (ITS); smart cities; vehicular ad hoc networks (VANETs); vehicular edge computing (VEC)
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El-Sayed, H.; Chaqfeh, M. Exploiting Mobile Edge Computing for Enhancing Vehicular Applications in Smart Cities. Sensors 2019, 19, 1073.

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