Federated learning for internet of things: A comprehensive survey
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
[HTML][HTML] Federated learning for 6G: Applications, challenges, and opportunities
Standard machine-learning approaches involve the centralization of training data in a data
center, where centralized machine-learning algorithms can be applied for data analysis and …
center, where centralized machine-learning algorithms can be applied for data analysis and …
When deep reinforcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5G ultradense …
Recently, smart cities, healthcare system, and smart vehicles have raised challenges on the
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …
A survey on security and privacy issues in edge-computing-assisted internet of things
Internet of Things (IoT) is an innovative paradigm envisioned to provide massive
applications that are now part of our daily lives. Millions of smart devices are deployed within …
applications that are now part of our daily lives. Millions of smart devices are deployed within …
Blockchain-based decentralized federated transfer learning methodology for collaborative machinery fault diagnosis
W Zhang, Z Wang, X Li - Reliability Engineering & System Safety, 2023 - Elsevier
Due to the limitations of data quality and quantity of a single industrial user, the development
of intelligent machinery fault diagnosis methods has been reaching a bottleneck in the …
of intelligent machinery fault diagnosis methods has been reaching a bottleneck in the …
EEDTO: An energy-efficient dynamic task offloading algorithm for blockchain-enabled IoT-edge-cloud orchestrated computing
With the proliferation of compute-intensive and delay-sensitive mobile applications, large
amounts of computational resources with stringent latency requirements are required on …
amounts of computational resources with stringent latency requirements are required on …
Fusion of federated learning and industrial Internet of Things: A survey
Abstract Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry
4.0 and paves an insight for new industrial era. Nowadays smart machines and smart …
4.0 and paves an insight for new industrial era. Nowadays smart machines and smart …
An adaptive federated learning scheme with differential privacy preserving
X Wu, Y Zhang, M Shi, P Li, R Li, NN Xiong - Future Generation Computer …, 2022 - Elsevier
Driven by the upcoming development of the sixth-generation communication system (6G),
the distributed machine learning schemes represented by federated learning has shown …
the distributed machine learning schemes represented by federated learning has shown …
Federated reinforcement learning: Techniques, applications, and open challenges
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL),
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …