Heterogeneous federated learning: State-of-the-art and research challenges
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …
scale industrial applications. Existing FL works mainly focus on model homogeneous …
Federated learning review: Fundamentals, enabling technologies, and future applications
Federated Learning (FL) has been foundational in improving the performance of a wide
range of applications since it was first introduced by Google. Some of the most prominent …
range of applications since it was first introduced by Google. Some of the most prominent …
Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
Holistic network virtualization and pervasive network intelligence for 6G
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …
solutions to replace the traditional model-driven approaches that proved to be not rich …
Federated learning for internet of things: Recent advances, taxonomy, and open challenges
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …
algorithm for both network and application management. However, given the presence of …
Federated learning: A survey on enabling technologies, protocols, and applications
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …
on enabling software and hardware platforms, protocols, real-life applications and use …
Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
Mobile edge intelligence for large language models: A contemporary survey
On-device large language models (LLMs), referring to running LLMs on edge devices, have
raised considerable interest since they are more cost-effective, latency-efficient, and privacy …
raised considerable interest since they are more cost-effective, latency-efficient, and privacy …
Federated learning for the internet of things: Applications, challenges, and opportunities
Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …