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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Proceedings ArticleDOI
A cross-layer design for QoS support in the 3GPP2 wireless systems
TL;DR: A suite of cross-layer design modules for QoS support in the 1/spl times/EV-DV system is proposed and the proposed dynamic resource allocation scheme is based on the effective capacity concept.
Journal ArticleDOI
Intelligent Task Offloading and Energy Allocation in the UAV-Aided Mobile Edge-Cloud Continuum
TL;DR: In this paper, a federated deep reinforcement learning (FDRL) framework is proposed to learn the joint task offloading and energy allocation decision while reducing the training cost and preventing privacy leakage of DRL training.
Book ChapterDOI
Deep Learning for EEG Motor Imagery-Based Cognitive Healthcare
TL;DR: A multiple-CNN feature fusion architecture to extract and fuse features by using subject-specific frequency bands and a cross-encoding technique has been proposed and is successfully used to train autoencoders for a novel cross-subject information transfer and augmenting EEG data.
Journal ArticleDOI
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
TL;DR: In this article, a real-time deep co-inference framework with IoT synergy was introduced to support resource and delay requirements of such paradigm, and a methodology aiming at distributing the DNN tasks onto the resource-constrained devices of the IoT system, while avoiding to reveal the model to participants.
Journal ArticleDOI
A new queuing strategy for large scale ATM switches
Mohsen Guizani,Ala Al-Fuqaha +1 more
TL;DR: A combined central and output queuing (CCOQ) technique is proposed to be used in designing large-scale ATM switches for high-speed networks.