A multi-agent federated reinforcement learning-based optimization of quality of service in various LoRa network slices

Article Computer Science, Information Systems

Exploring Deep-Reinforcement-Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Preserving EdgeIoT

Jingjing Zheng et al.

Summary: This article investigates the problem of protecting data training privacy in the Internet of Things. By selecting IoT devices with different data set sizes, the balance between learning accuracy and energy consumption can be achieved. The authors propose a new framework to balance the accuracy and energy consumption of FL, and leverage LSTM to predict network state.

IEEE INTERNET OF THINGS JOURNAL (2022)

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Article Automation & Control Systems

Deep Federated Q-Learning-Based Network Slicing for Industrial IoT

Seifeddine Messaoud et al.

Summary: The article discusses the importance of network slicing in enabling IIoT networks with multiservices and resource requirements, and introduces federated reinforcement learning as a promising approach for distributed data acquisition and computation tasks. The proposed deep RL scheme aims to provide federated and dynamic network management and resource allocation for differentiated QoS services in future IIoT networks, achieving efficient performance compared to traditional approaches.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

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Article Computer Science, Information Systems

Survey on Network Slicing for Internet of Things Realization in 5G Networks

Shalitha Wijethilaka et al.

Summary: Network slicing is a key technology in 5G architecture that enables the realization of IoT, dividing the physical network into multiple logical networks with different characteristics to meet diverse networking demands. This survey provides a comprehensive analysis of network slicing's utilization in IoT, addressing technical challenges and discussing integration challenges and open research problems. Integration of other emerging technologies like blockchain and AI/ML in network slicing and IoT integration is also explored.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2021)

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Article Automation & Control Systems