Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Distributed learning based on 1-bit gradient coding in the presence of stragglers
C Li, M Skoglund - IEEE Transactions on Communications, 2024 - ieeexplore.ieee.org
This paper considers the problem of distributed learning (DL) in the presence of stragglers.
For this problem, DL methods based on gradient coding have been widely investigated …
For this problem, DL methods based on gradient coding have been widely investigated …
Online distributed learning over random networks
The recent deployment of multi-agent systems in a wide range of scenarios has enabled the
solution of learning problems in a distributed fashion. In this context, agents are tasked with …
solution of learning problems in a distributed fashion. In this context, agents are tasked with …
FLSTRA: Federated learning in stratosphere
We propose a federated learning (FL) in stratosphere (FLSTRA) system, where a high
altitude platform station (HAPS) facilitates a large number of terrestrial clients to …
altitude platform station (HAPS) facilitates a large number of terrestrial clients to …
Multiple Access in the Era of Distributed Computing and Edge Intelligence
This paper focuses on the latest research and innovations in fundamental next-generation
multiple access (NGMA) techniques and the coexistence with other key technologies for the …
multiple access (NGMA) techniques and the coexistence with other key technologies for the …
Adaptive Top-K in SGD for Communication-Efficient Distributed Learning in Multi-Robot Collaboration
Distributed stochastic gradient descent (D-SGD) with gradient compression has become a
popular communication-efficient solution for accelerating optimization procedures in …
popular communication-efficient solution for accelerating optimization procedures in …
Multi-Dimensional Resource Management for Distributed MEC Networks in Jamming Environment: A Hierarchical DRL Approach
This article investigates the problem of multidimensional resource management in
multiaccess mobile edge computing (MEC) networks against external dynamic jamming …
multiaccess mobile edge computing (MEC) networks against external dynamic jamming …
Best Response Dynamics Convergence for Generalised Nash Equilibrium Problems: An Opportunity for Autonomous Multiple Access Design in Federated Learning
G Thiran, I Stupia… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning (FL) is envisioned to be a key enabler of network functionalities based
on artificial intelligence. Multiple access mechanisms supporting the learning task must then …
on artificial intelligence. Multiple access mechanisms supporting the learning task must then …
Improving network data security interaction methods under wireless communication
J Geng - Internet Technology Letters, 2024 - Wiley Online Library
With the development of information technology, network data security issues have received
widespread attention. Under traditional wired communication networks, it not only has high …
widespread attention. Under traditional wired communication networks, it not only has high …
[HTML][HTML] DISTRIBUTED RESOURCE OPTIMISATION USING THE Q-LEARNING ALGORITHM, IN DEVICE-TO-DEVICE COMMUNICATION: A REINFORCEMENT …
S Jayakumar, S Nandakumar - Results in Engineering, 2024 - Elsevier
In the context of wireless systems going forward, particularly in the Beyond 5G (B5G) era,
where high data rates and low latency are critical, D2D communication is a pivotal …
where high data rates and low latency are critical, D2D communication is a pivotal …