Documents dont l'auteur est "Mlika, Zoubeir"

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Abouaomar, A., Cherkaoui, S., Mlika, Z., & Kobbane, A. (2022). Service Function Chaining in MEC: A Mean-Field Game and Reinforcement Learning Approach. IEEE Systems Journal, 16(4), 5357-5368. Lien externe

Abouaomar, A., Mlika, Z., Filali, A., Cherkaoui, S., & Kobbane, A. (octobre 2021). A Deep Reinforcement Learning Approach for Service Migration in MEC-enabled Vehicular Networks [Communication écrite]. 46th IEEE Conference on Local Computer Networks (LCN 2021), Edmonton, Alberta, Canada. Lien externe

Abouaomar, A., Cherkaoui, S., Mlika, Z., & Kobbane, A. (décembre 2021). Mean-field game and reinforcement learning MEC resource provisioning for SFC [Communication écrite]. IEEE Global Communications Conference (IEEE GLOBAL 2021), Madrid, Spain. Lien externe

Abouaomar, A., Cherkaoui, S., Mlika, Z., & Kobbane, A. (2021). Resource Provisioning in Edge Computing for Latency Sensitive Applications. IEEE Internet of Things Journal, 8(14), 11088-11099. Lien externe

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Filali, A., Mlika, Z., & Cherkaoui, S. (2024). Open RAN Slicing for MVNOs With Deep Reinforcement Learning. IEEE Internet of Things Journal, 3365665 (15 pages). Lien externe

Filali, A., Mlika, Z., Cherkaoui, S., & Kobbane, A. (2022). Dynamic SDN-based radio access network slicing with deep reinforcement learning for URLLC and eMBB services. IEEE Transactions on Network Science and Engineering, 9(4), 2174-2187. Lien externe

Filali, A., Mlika, Z., Cherkaoui, S., & Kobbane, A. (2020). Preemptive SDN Load Balancing with Machine Learning for Delay Sensitive Applications. IEEE Transactions on Vehicular Technology, 69(12), 15947-15963. Lien externe

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Hojatian, H., Mlika, Z., Nadal, J., Frigon, J.-F., & Leduc-Primeau, F. (2024). Learning energy-efficient transmitter configurations for massive MIMO beamforming. IEEE Transactions on Machine Learning in Communications and Networking, 2, 939-955. Disponible

Hentati, A., Mlika, Z., Frigon, J.-F., & Ajib, W. (avril 2022). Energy Harvesting Wireless Sensor Networks: Inter-delivery-aware Scheduling Algorithms [Communication écrite]. 2022 IEEE Wireless Communications and Networking Conference (WCNC 2022), Austin, TX, USA. Lien externe

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Mlika, Z., Do, T. N., Larabi, A., Vo, J. D., Frigon, J.-F., & Leduc-Primeau, F. (octobre 2024). Online energy-efficient beam bandwidth partitioning in mmwave mobile networks [Communication écrite]. IEEE 100th Vehicular Technology Conference (VTC2024-Fall), Washington, DC, USA (6 pages). Lien externe

Mlika, Z., Cherkaoui, S., Laprade, J. F., & Corbeil-Letourneau, S. (2023). User trajectory prediction in mobile wireless networks using quantum reservoir computing. IET Quantum Communication, 4(3), 125-135. Disponible

Mlika, Z., & Cherkaoui, S. (2022). Deep deterministic policy gradient to minimize the age of information in cellular V2X communications. IEEE Transactions on Intelligent Transportation Systems, 23(12), 23597-23612. Lien externe

Moudoud, H., Mlika, Z., Khoukhi, L., & Cherkaoui, S. (2022). Detection and Prediction of FDI Attacks in IoT Systems via Hidden Markov Model. IEEE Transactions on Network Science and Engineering, 9(5), 2978-2990. Lien externe

Mlika, Z., & Cherkaoui, S. (juin 2021). Competitive Algorithms and Reinforcement Learning for NOMA in IoT Networks [Communication écrite]. IEEE International Conference on Communications (ICC 2021), Montreal, Qc, Canada (6 pages). Lien externe

Mlika, Z., & Cherkaoui, S. (2021). Massive IoT Access with NOMA in 5G Networks and Beyond using Online Competitiveness and Learning. IEEE Internet of Things Journal, 8(17), 13624-13639. Lien externe

Mlika, Z., & Cherkaoui, S. (2021). Network slicing for vehicular communications: a multi-agent deep reinforcement learning approach. Lien externe

Mlika, Z., & Cherkaoui, S. (2021). Network Slicing with MEC and Deep Reinforcement Learning for the Internet of Vehicles. IEEE Network, 35(3), 132-138. Lien externe

Mlika, Z., Ajib, W., Jaafar, W., & Haccoun, D. (septembre 2012). On the performance of relay selection in cognitive radio networks [Communication écrite]. 76th IEEE Vehicular Technology Conference, VTC Fall 2012, Québec City, QC, Canada. Lien externe

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Nour, B., Cherkaoui, S., & Mlika, Z. (2022). Federated Learning and Proactive Computation Reuse at the Edge of Smart Homes. IEEE Transactions on Network Science and Engineering, 9(5), 3045-3056. Lien externe

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Triwinarko, A., Mlika, Z., Cherkaoui, S., & Dayoub, I. (octobre 2022). Deep Reinforcement Learning to Improve Vehicle-to-Vulnerable Road User Communications in C-V2X [Communication écrite]. 8th International Symposium on ubiquitous Networking (UNeT 2022), Montreal, Qc, Canada. Lien externe

Taik, A., Mlika, Z., & Cherkaoui, S. (2022). Clustered Vehicular Federated Learning: Process and Optimization. IEEE Transactions on Intelligent Transportation Systems, 23(12), 25371-25383. Lien externe

Taïk, A., Mlika, Z., & Cherkaoui, S. (2022). Data-Aware Device Scheduling for Federated Edge Learning. IEEE Transactions on Cognitive Communications and Networking, 8(1), 408-421. Lien externe