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
More filters
Proceedings ArticleDOI
Haddle: A Framework for Investigating Data Leakage Attacks in Hadoop
TL;DR: This paper presents a typical data leakage attack scene in Hadoop and proposes Haddle (Hadoop Data Leakage Explorer), a forensic framework composed of automatic analytical methods and on-demand data collection based on two stages.
Proceedings ArticleDOI
Entropy-based Fuzzy AHP Model for Trustworthy Service Provider Selection in Internet of Things
Abdelmuttlib Ibrahim Abdalla Ahmed,Suleman Khan,Abdullah Gani,Siti Hafizah Ab Hamid,Mohsen Guizani +4 more
TL;DR: This work introduces Entropy-based fuzzy analytic hierarchy process (EFAHP) as a trust model for selecting a trustworthy service provider, since the sense of decision making regarding multi-metrics trust is structural.
Journal ArticleDOI
Achieving Energy Efficiency and Sustainability in Edge/Fog Deployment
Neeraj Kumar,Joel J. P. C. Rodrigues,Mohsen Guizani,Kim-Kwang Raymond Choo,Rongxing Lu,Christos Verikoukis,Zhimeng Zhong +6 more
TL;DR: This Feature Topic, state-of-the-art research advances in energy efficiency and sustainability for edge/fog deployment are presented.
Journal ArticleDOI
Improving flow delivery with link available time prediction in software-defined high-speed vehicular networks
TL;DR: This paper proposes a link available time prediction based backup caching and routing (LBR) scheme in software-defined high-speed vehicular networks and explores the benefit and cost of the backup caching compared with link prediction based routing (LR) algorithm.
Proceedings ArticleDOI
UAV Placement Optimization for Internet of Medical Things.
TL;DR: A particle swarm optimization (PSO) based algorithm to optimize the UAV placement over the serving area for the IoMT devices is proposed and results show that the approach can significantly reduce the number of UAVs needed to deploy while considering the communication coverage and other factors.