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
Journal ArticleDOI
A blockchain-based architecture for secure vehicular Named Data Networks
Hakima Khelifi,Senlin Luo,Boubakr Nour,Hassine Moungla,Hassine Moungla,Syed Hassan Ahmed,Mohsen Guizani +6 more
TL;DR: This paper proposes a reputation-based Blockchain mechanism to secure both of Interest and Data forwarding plane, and content caching, and results exhibit that the solution forwards only valid Interest and caches only trust content.
Journal ArticleDOI
Impact of Channel Estimation Error on Bidirectional MABC-AF Relaying With Asymmetric Traffic Requirements
TL;DR: A robust and practical optimum power-allocation algorithm that minimizes the system outage probability under aggregate and individual node power constraints is developed and the proposed relay selection criterion is superior to the classical max–min criterion with ATRs, and the performance improvement becomes remarkable as channel estimation error increases.
Journal ArticleDOI
SDN Controllers: A Comprehensive Analysis and Performance Evaluation Study
TL;DR: This work uses three benchmarking tools to compare 9 controllers and presents a detailed analysis of their performance, along with discussion on performance of specialized network controllers.
Journal ArticleDOI
Joint Interference Management in Ultra-Dense Small-Cell Networks: A Multi-Domain Coordination Perspective
TL;DR: The proposed distributed joint interference management (JIM) algorithm allows each small-cell base station to self-organize and interact into a stable overlapping coalition structure and reduce interference gradually from multi-domain, thus achieving an optimal tradeoff between costs and benefits.
Journal ArticleDOI
Trust-Based Cloud Machine Learning Model Selection for Industrial IoT and Smart City Services
TL;DR: The proposed heuristic comprises an intelligent polynomial-time heuristic that maximizes the level of trust of ML models by selecting and switching between a subset of the ML models from a superset of models in order to maximize the trustworthiness while respecting the given reconfiguration budget/rate and reducing the cloud communication overhead.