Chapters authored
Network Slicing for Industrial IoT and Industrial Wireless Sensor Network: Deep Federated Learning Approach and Its Implementation Challenges
5G networks are envisioned to support heterogeneous Industrial IoT (IIoT) and Industrial Wireless Sensor Network (IWSN) applications with a multitude Quality of Service (QoS) requirements. Network slicing is being recognized as a beacon technology that enables multi-service IIoT networks. Motivated by the growing computational capacity of the IIoT and the challenges of meeting QoS, federated reinforcement learning (RL) has become a propitious technique that gives out data collection and computation tasks to distributed network agents. This chapter discuss the new federated learning paradigm and then proposes a Deep Federated RL (DFRL) scheme to provide a federated network resource management for future IIoT networks. Toward this goal, the DFRL learns from Multi-Agent local models and provides them the ability to find optimal action decisions on LoRa parameters that satisfy QoS to IIoT virtual slice. Simulation results prove the effectiveness of the proposed framework compared to the early tools.
Part of the book: Emerging Trends in Wireless Sensor Networks
Future Internet of Things: Connecting the Unconnected World and Things Based on 5/6G Networks and Embedded Technologies
Undeniably, the Internet of Things (IoT) ecosystem keeps on advancing at a fast speed, far above all predictions for growth and ubiquity. From sensor to cloud, this massive network continues to break technical limits in a variety of ways, and wireless sensor nodes are likely to become more prevalent as the number of Internet of Things devices increases into the trillions to connect the world and unconnected objects. However, their future in the IoT ecosystem remains uncertain, as various difficulties as with device connectivity, edge artificial intelligence (AI), security and privacy concerns, increased energy demands, the right technologies to use, and continue to attract opposite forces. This chapter provides a brief, forward-looking overview of recent trends, difficulties, and cutting-edge solutions for low-end IoT devices that use reconfigurable computing technologies like FPGA SoC and next-generation 5/6G networks. Tomorrow’s IoT devices will play a critical role. At the end of this chapter, an edge FPGA SoC computing-based IoT application is proposed, to be a novel edge computing for IoT solution with low power consumption and accelerated processing capability in data exchange.
Part of the book: Internet of Things