A Traffic-Aware Approach for Enabling Unmanned Aerial Vehicles (UAVs) in Smart City Scenarios

Hesham El-Sayed, Moumena Chaqfa, Sherali Zeadally, Deepak Puthal

    Research output: Contribution to journalArticlepeer-review

    33 Citations (Scopus)


    In smart cities, vehicular applications require high computation capabilities and low-latency communication. Edge computing offers promising solutions for addressing these requirements because of several features, such as geo-distribution, mobility, low latency, heterogeneity, and support for real-time interactions. To employ network edges, existing fixed roadside units can be equipped with edge computing servers. Nevertheless, there are situations where additional infrastructure units are required to handle temporary high traffic loads during public events, unexpected weather conditions, or extreme traffic congestion. In such cases, the use of flying roadside units are carried by unmanned aerial vehicles (UAVs), which provide the required infrastructure for supporting traffic applications and improving the quality of service. UAVs can be dynamically deployed to act as mobile edges in accordance with traffic events and congestion conditions. The key benefits of this dynamic approach include: 1) the potential for characterizing the environmental requirements online and performing the deployment accordingly, and 2) the ability to move to another location when necessary. We propose a traffic-aware method for enabling the deployment of UAVs in vehicular environments. Simulation results show that our proposed method can achieve full network coverage under different scenarios without extra communication overhead or delay.

    Original languageEnglish
    Article number8735690
    Pages (from-to)86297-86305
    Number of pages9
    JournalIEEE Access
    Publication statusPublished - 2019


    • Edge computing
    • flying RSUs
    • intelligent transportation systems
    • unmanned aerial vehicles
    • vehicular networks

    ASJC Scopus subject areas

    • General Computer Science
    • General Materials Science
    • General Engineering


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