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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Journal ArticleDOI
Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
Ihab Mohammed,Shadha Tabatabai,Ala Al-Fuqaha,Faissal El Bouanani,Junaid Qadir,Basheer Qolomany,Mohsen Guizani +6 more
TL;DR: This work solves the problem of optimizing accuracy in stateful FL with a budgeted number of candidate clients by selecting the best candidate clients in terms of test accuracy to participate in the training process and proposed heuristic outperforms the online random algorithm with up to 27% gain in accuracy.
Book
Network Modeling and Simulation: A Practical Perspective
TL;DR: This chapter discusses the design and implementation of a Discrete-Event Simulation Framework, a framework for simulating networks, and some of the techniques used in this framework, including CASiNO, which was developed in this chapter.
Posted Content
When Energy Trading meets Blockchain in Electrical Power System: The State of the Art
TL;DR: In this paper, a survey of the blockchain-based energy trading in electrical power system is thoroughly investigated and the existing energy trading schemes are studied and classified into three categories based on their main focus: energy transaction, consensus mechanism, and system optimization.
Journal ArticleDOI
Blockchain-Based Anonymous Authentication With Selective Revocation for Smart Industrial Applications
TL;DR: An efficient selective revocation mechanism is proposed based on dynamic accumulators and the signature algorithm due to Pointcheval and Sanders as the overlay of the BASS for smart industrial applications supporting attribute privacy, selective revocation, credential soundness, and multishowing-unlinkability.
Journal ArticleDOI
A Spark-Based Parallel Fuzzy $c$ -Means Segmentation Algorithm for Agricultural Image Big Data
TL;DR: It is indicated that the Spark-based parallel FCM algorithm provides faster speed of segmentation for agricultural image big data and has better scale-up and size-up rates.