M
Mohsen Guizani
Researcher at Qatar University
Publications - 1337
Citations - 48275
Mohsen Guizani is an academic researcher from Qatar University. The author has contributed to research in topics: Computer science & Cloud computing. The author has an hindex of 79, co-authored 1110 publications receiving 31282 citations. Previous affiliations of Mohsen Guizani include Jaypee Institute of Information Technology & University College for Women.
Papers
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Replisom : Disciplined Tiny Memory Replication for Massive IoT Devices in LTE Edge Cloud
TL;DR: The analysis and numerical evaluation suggest that the proposed Replisom system has significant potential in reducing the delay, energy consumption, and cost for cloud offloading of IoT applications given the massive number of devices with tiny memory sizes.
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Offloading Time Optimization via Markov Decision Process in Mobile-Edge Computing
TL;DR: This work first investigates a MEC system consisting of mobile devices and heterogeneous edge severs that support various radio access technologies, and proposes an optimal offloading node selection strategy formulated as a Markov decision process (MDP), and solved by employing the value iteration algorithm (VIA).
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Cooperative earth observation through complex space information networks
TL;DR: This article discusses the current space-based networking technology and inter-satellite routings, and addresses the cooperative Earth observation model of the SBIN, and presents research results.
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Spammer Detection and Fake User Identification on Social Networks
Faiza Masood,Ghana Ammad,Ahmad Almogren,Assad Abbas,Hasan Ali Khattak,Ikram Ud Din,Mohsen Guizani,Mansour Zuair +7 more
TL;DR: A taxonomy of the Twitter spam detection approaches is presented that classifies the techniques based on their ability to detect: (i) fake content, (ii) spam based on URL, (iii) spam in trending topics, and (iv) fake users.
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A Distributed Framework for Energy Trading Between UAVs and Charging Stations for Critical Applications
TL;DR: Numerical analysis shows that the proposed model helps in providing increased utility for the swarm of UAVs and charging stations in a secure and cost-optimal way as compared to the conventional schemes.