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
Release-time aware VM placement
TL;DR: This paper proposes several extensions to the original BF heuristic by accounting for VMs' release times when making VM placement decisions that reduces energy consumption and enhances utilization of cloud servers.
Journal ArticleDOI
An Energy Aware Offloading Scheme for Interdependent Applications in Software-Defined IoV With Fog Computing Architecture
TL;DR: An energy-aware dynamic offloading scheme is proposed to prolong the running time of the IoV system by leveraging available battery power to execute more applications under the constraints of application dependence.
Journal ArticleDOI
Chain-based big data access control infrastructure
Emmanuel Boateng Sifah,Qi Xia,Kwame Opuni-Boachie Obour Agyekum,Sandro Amofa,Jianbin Gao,Ruidong Chen,Hu Xia,James C. Gee,James C. Gee,Xiaojiang Du,Mohsen Guizani +10 more
TL;DR: An off-chain-based sovereign blockchain is proposed, where a virtual container is created for parties to transact in, and at the end of a transaction, the container is destroyed but the results are stored on the sovereign blockchain network.
Journal ArticleDOI
A Heuristic Statistical Testing Based Approach for Encrypted Network Traffic Identification
TL;DR: This paper proposed a heuristic statistical testing (HST) approach that combines both statistics and machine learning and has been proved to alleviate their respective deficiencies and showed that C4.5, with the method, has the highest identification accuracy for secure sockets layer and secure shell traffic.
Journal ArticleDOI
Contract and Lyapunov Optimization-Based Load Scheduling and Energy Management for UAV Charging Stations
TL;DR: An online algorithm based on Lyapunov optimization is proposed to schedule the charging of UAVs and the energy management of the charging station, and can improve the efficiency of charging station operators, allowing users to avoid charging at peak times, and only use real-time information to schedule UAV's.