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09/03/2023
A Comparative Evaluation of FedAvg and Per-FedAvg Algorithms for Dirichlet Distributed Heterogeneous Data
In this paper, we investigate Federated Learning (FL), a paradigm of mac...
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08/04/2023
Vehicles Control: Collision Avoidance using Federated Deep Reinforcement Learning
In the face of growing urban populations and the escalating number of ve...
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01/30/2023
Federated Learning for Water Consumption Forecasting in Smart Cities
Water consumption remains a major concern among the world's future chall...
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02/13/2022
Communication and Computation O-RAN Resource Slicing for URLLC Services Using Deep Reinforcement Learning
The evolution of the future beyond-5G/6G networks towards a service-awar...
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02/13/2022
Dynamic SDN-based Radio Access Network Slicing with Deep Reinforcement Learning for URLLC and eMBB Services
Radio access network (RAN) slicing is a key technology that enables 5G n...
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01/27/2022
Resource Provisioning in Edge Computing for Latency Sensitive Applications
Low-Latency IoT applications such as autonomous vehicles, augmented/virt...
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01/27/2022
A Deep Reinforcement Learning Approach for Service Migration in MEC-enabled Vehicular Networks
Multi-access edge computing (MEC) is a key enabler to reduce the latency...
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01/27/2022
Mean-Field Game and Reinforcement Learning MEC Resource Provisioning for SFC
In this paper, we address the resource provisioning problem for service ...
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01/27/2022
A Resources Representation For Resource Allocation In Fog Computing Networks
Fog computing is emerging as a new paradigm to deal with latency-sensiti...
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01/27/2022
Matching-Game for User-Fog Assignment
Fog computing has emerged as a new paradigm in mobile network communicat...
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05/10/2021
