Decentralized learning (DL) has gained prominence for its potential benefits in terms of
scalability, privacy, and fault tolerance. It consists of many nodes that coordinate without a …

Currently, one of the simplest and most effective ways for people to gain an in-depth
understanding of computer networks is through hands-on practice and experimentation on …

Prototyping and implementing distributed algorithms, particularly those that address
challenges related with fault-tolerance and dependability, is a time consuming task. This is …

Several sources of randomness can change the radio link data rate at the edge of tactical
networks. Simulations and field experiments define these sources of randomness indirectly …

Regular expression denial of service (ReDoS) is an asymmetric cyberattack that has
become prominent in recent years. Many research works examine ReDoS, measuring its …

The novel blockchain generation of Byzantine fault-tolerant (BFT) state machine replication
(SMR) protocols focuses on scalability and performance to meet the requirements of …

We introduce an open-source, scalable, and distributed architecture, called Megalos, that
supports the implementation of virtual network scenarios consisting of virtual devices (VDs) …

Novel Byzantine fault-tolerant (BFT) state machine replication protocols improve scalability
for their practical use in distributed ledger technology, where hundreds of replicas must …

Vehicular cooperation taking place in Intelligent Transportation Systems (ITS) aims to solve
traffic issues or to improve road safety for vehicles and vulnerable road users. Such …

Decentralized learning (DL) is an emerging technique that allows nodes on the web to
collaboratively train machine learning models without sharing raw data. Dealing with …