Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
[HTML][HTML] Privacy-enhancing technologies in federated learning for the internet of healthcare things: a survey
Advancements in wearable medical devices using the IoT technology are shaping the
modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT) …
modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT) …
A survey on secure and private federated learning using blockchain: Theory and application in resource-constrained computing
E Moore, A Imteaj, S Rezapour… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has gained widespread popularity in recent years due to the fast
booming of advanced machine learning and artificial intelligence, along with emerging …
booming of advanced machine learning and artificial intelligence, along with emerging …
Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions
Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart
services and innovative applications. Such a context urges a heavy usage of Machine …
services and innovative applications. Such a context urges a heavy usage of Machine …
Federated learning using game strategies: State-of-the-art and future trends
R Gupta, J Gupta - Computer Networks, 2023 - Elsevier
Federated learning (FL) is a new and promising paradigm that allows devices to learn
without sharing data with the centralized server. It is often built on decentralized data where …
without sharing data with the centralized server. It is often built on decentralized data where …
High-Precision Cluster Federated Learning for Smart Home: An Edge-Cloud Collaboration Approach
Owing to the strong protection of data privacy, federated learning (FL) has become a key
method to achieve intelligent decision making in smart homes. However, under realistic …
method to achieve intelligent decision making in smart homes. However, under realistic …
HSFL: Efficient and privacy-preserving offloading for split and federated learning in IoT services
Distributed machine learning methods like Federated Learning (FL) and Split Learning (SL)
meet the growing demands of processing large-scale datasets under privacy restrictions …
meet the growing demands of processing large-scale datasets under privacy restrictions …
Machine learning enabled network and task management in SDN based Fog architecture
Abstract Effective communication among Fog Computing resources is crucial concerning the
network's diverse Quality of Service (QoS) parameters. However, while Fog nodes may be …
network's diverse Quality of Service (QoS) parameters. However, while Fog nodes may be …
A blockchain-assisted intelligent edge cooperation system for IoT environments with multi-infrastructure providers
X Du, X Chen, Z Lu, Q Duan, Y Wang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
While edge computing has the potential to offer low-latency services and overcome the
limitations of traditional cloud computing, it presents new challenges in terms of trust …
limitations of traditional cloud computing, it presents new challenges in terms of trust …
[HTML][HTML] Personalized Fair Split Learning for Resource-Constrained Internet of Things
H Chen, X Chen, L Peng, Y Bai - Sensors, 2023 - mdpi.com
With the flourishing development of the Internet of Things (IoT), federated learning has
garnered significant attention as a distributed learning method aimed at preserving the …
garnered significant attention as a distributed learning method aimed at preserving the …