Mhd Saria Allahham
Orcid: 0000-0002-3883-2588
According to our database1,
Mhd Saria Allahham authored at least 21 papers
between 2020 and 2026.
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Bibliography
2026
How Reliable is Your Service at the Extreme Edge? Analytical Modeling of Computational Reliability.
CoRR, February, 2026
DRONE-RL: Dynamic reinforcement learning for online navigation of UAVs in evolving environments.
Knowl. Based Syst., 2026
Proceedings of the 23rd Consumer Communications & Networking Conference, 2026
2024
Proceedings of the 2024 IEEE Global Communications Conference, 2024
Proceedings of the 2024 IEEE Global Communications Conference, 2024
2023
Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks.
IEEE Commun. Mag., February, 2023
Proceedings of the IEEE International Conference on Communications, 2023
2022
IEEE Trans. Netw. Sci. Eng., 2022
Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks.
IEEE Trans. Cogn. Commun. Netw., 2022
Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022
Proceedings of the 5th International Conference on Communications, 2022
2021
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning.
IEEE Internet Things J., 2021
Motivating Learners in Multi-Orchestrator Mobile Edge Learning: A Stackelberg Game Approach.
CoRR, 2021
IEEE Access, 2021
Proceedings of the IEEE International Conference on Communications Workshops, 2021
ONSRA: an Optimal Network Selection and Resource Allocation Framework in multi-RAT Systems.
Proceedings of the ICC 2021, 2021
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning.
Proceedings of the IEEE Global Communications Conference, 2021
Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning.
Proceedings of the IEEE Global Communications Conference, 2021
2020
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach.
Proceedings of the IEEE International Conference on Informatics, 2020