no code implementations • 19 Jan 2024 • Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non independent and identically distributed (non IID) data across multiple users.
no code implementations • 11 Jan 2024 • Nima Abdi, Abdullatif Albaseer, Mohamed Abdallah
{ This is followed by a critical discussion on their practical implications and broader impact on cybersecurity in Smart Grids.}
no code implementations • 5 Oct 2023 • Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha
This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating pro-social applications.
no code implementations • 2 Nov 2022 • Shawqi Al-Maliki, Faissal El Bouanani, Mohamed Abdallah, Junaid Qadir, Ala Al-Fuqaha
Data distribution shift is a common problem in machine learning-powered smart city applications where the test data differs from the training data.
no code implementations • 29 Apr 2022 • Shadha Tabatabai, Ihab Mohammed, Basheer Qolomany, Abdullatif Albasser, Kashif Ahmad, Mohamed Abdallah, Ala Al-Fuqaha
The remaining cluster with surviving clients is then used for training the best FL model (i. e., remaining FL model).
no code implementations • 28 Feb 2022 • Abdulmalik Alwarafy, Bekir Sait Ciftler, Mohamed Abdallah, Mounir Hamdi, Naofal Al-Dhahir
This paper considers the problem of cost-aware downlink sum-rate maximization via joint optimal radio access technologies (RATs) assignment and power allocation in next-generation heterogeneous wireless networks (HetNets).
no code implementations • 16 Aug 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Extensive experiments show that the proposed approach lowers the training time and accelerates the convergence rate by up to 50% while imbuing each client with a specialized model that is fit for its local data distribution.
no code implementations • 13 Jul 2021 • Marwan Dhuheir, Abdullatif Albaseer, Emna Baccour, Aiman Erbad, Mohamed Abdallah, Mounir Hamdi
Recognizing the patient's emotions using deep learning techniques has attracted significant attention recently due to technological advancements.
no code implementations • 20 Jun 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Specifically, we consider a problem that aims to find the optimal user's resources, including the fine-grained selection of relevant training samples, bandwidth, transmission power, beamforming weights, and processing speed with the goal of minimizing the total energy consumption given a deadline constraint on the communication rounds of FEEL.
no code implementations • 25 May 2021 • Abdulmalik Alwarafy, Mohamed Abdallah, Bekir Sait Ciftler, Ala Al-Fuqaha, Mounir Hamdi
In this paper, we conduct a systematic in-depth, and comprehensive survey of the applications of DRL techniques in RRAM for next generation wireless networks.
no code implementations • 3 Apr 2021 • Muhammad Shehab, Bekir S. Ciftler, Tamer Khattab, Mohamed Abdallah, Daniele Trinchero
In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) scenario with the aim of maximizing the sum rate of users.
no code implementations • 30 Mar 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Then, the problem is formulated as joint energy minimization and resource allocation optimization problem to obtain the optimal local computation time and the optimal transmission time that minimize the total energy consumption considering the worker's energy budget, available bandwidth, channel states, beamforming, and local CPU speed.
1 code implementation • 4 Feb 2020 • Lina Alsahan, Noureddine Lasla, Mohamed Abdallah
This paper presents a new blockchain network simulator that uses bitcoin's original reference implementation as its main application.
Cryptography and Security
no code implementations • 10 Jan 2020 • Abdullatif Albaseer, Bekir Sait Ciftler, Mohamed Abdallah, Ala Al-Fuqaha
The algorithm is divided into two phases where the first phase trains a global model based on the labeled data.
no code implementations • 7 Jan 2020 • Bekir Sait Ciftler, Abdullatif Albaseer, Noureddine Lasla, Mohamed Abdallah
Although crowdsourcing is an excellent way to gather immense amounts of data, it jeopardizes the privacy of participants, as it requires to collect labeled data at a centralized server.
no code implementations • 24 Dec 2019 • Mohamed Baza, Andrew Salazar, Mohamed Mahmoud, Mohamed Abdallah, Kemal Akkaya
In this paper, we tackle this problem by sharing the models instead of the original sensitive data by using the mimic learning approach.