Vehicular ad hoc networks (VANETs) is one of the most promising approaches for the
Intelligent Transportation Systems (ITS). With the rapid increase in the amount of traffic data …

Federated machine learning (Fed ML) is a new distributed machine learning technique
using clients' local data applied to collaboratively train a global model without transmitting …

Machine learning (ML) is a promising enabler for the fifth generation (5G) communication
systems and beyond. By imbuing intelligence into the network edge, edge nodes can …

Although the field of distributed optimization is well developed, relevant literature focused on
the application of distributed optimization to multi-robot problems is limited. This survey …

Private networks will play a key role in 5G and beyond to enable smart factories with the
required better deployment, operation and flexible usage of available resource and …

Secure model aggregation across many users is a key component of federated learning
systems. The state-of-the-art protocols for secure model aggregation, which are based on …

In this paper we study the distributed average consensus problem in multi-agent systems
with dynamically-changing directed communication links that are subject to quantized …

In this paper, a new communication-efficient federated learning (FL) framework is proposed,
inspired by vector quantized compressed sensing. The basic strategy of the proposed …

An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can
collaboratively execute semi-autonomous IoT applications, examples of which include …

Recently, federated learning (FL) has sparked widespread attention as a promising
decentralized machine learning approach which provides privacy and low delay. However …