Maggie Ezzat Gaber Gendy , MS.

Senior TA.

Field of Interest
Office Hours


  • Auctions have been employed as an effective framework
    for the management and the assignment of tasks in mobile
    crowdsensing (MCS). In auctions terminology, the clearance
    rate (CR) refers to the percentage of items that are sold
    over the duration of the auction. This research is concerned
    with maximizing the CR of reputation-aware (RA) auctions in
    centralized, participatory MCS systems. Recent techniques in the
    literature had focused on several challenges including untruthful
    bidding and malicious information that might be sent by the
    participants. Less attention has been given, though, to the number
    of completed tasks in such systems, even though it has a tangible
    impact on the satisfaction of service demanders. Towards the
    goal of maximizing CR in MCS systems, we propose two new
    formulations for the bidding procedure that is a part of the
    task allocation strategy. Simulations were carried out to evaluate
    the proposed methods and their impact on the user utility,
    under varying number of auctions, tasks, and participants. We
    demonstrate the effectiveness of the suggested methods through
    consistent and considerable increases (three times increase, in
    some cases) in the CR compared to the state-of-the-art.

Spring - 2017
Sunday 9am 10am


  • Master in Electronics and Communications, Arab Academy, Jan 2016

List of Publications

    • Ehab Farouk Badran Ahmed Fatahy Mohammed Alkabbany, "Maximizing Clearance Rate of Reputation-aware Auctions in Mobile Crowdsensing" , Accepted to appear in CCNC, 2019. , 2019.
            Read Abstract Download PDF

Fields of Interest

  • cloud computing

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