activity
20202023
most citedShort-Term Flow-Based Bandwidth Forecasting using Machine Learning

5 citations · 6 across the 4 of their papers we have counts for

collaborators

6 papers

cs.NI2023★ 1 cited

Software defined networking flow admission and routing under minimal security constraints

Jorge López, Charalampos Chatzinakis, Marc Cartigny +1

In recent years, computer networks and telecommunications in general have been shifting paradigms to adopt software-centric approaches. Software Defined Networking (SDN) is one of…

cs.SE2021

Toward Formal Data Set Verification for Building Effective Machine Learning Models

Jorge López, Maxime Labonne, Claude Poletti

In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain pro…

cs.NI2021

Dynamic Link Network Emulation: a Model-based Design

Erick Petersen, Jorge López, Natalia Kushik +2

This paper presents the design and architecture of a network emulator whose links' parameters (such as delay and bandwidth) vary at different time instances. The emulator can thus…

cs.NI2020★ 5 cited

Short-Term Flow-Based Bandwidth Forecasting using Machine Learning

Maxime Labonne, Jorge López, Claude Poletti +1

This paper proposes a novel framework to predict traffic flows' bandwidth ahead of time. Modern network management systems share a common issue: the network situation evolves betwe…

cs.SE2020

On using SMT-solvers for Modeling and Verifying Dynamic Network Emulators

Erick Petersen, Jorge López, Natalia Kushik +2

A novel model-based approach to verify dynamic networks is proposed; the approach consists in formally describing the network topology and dynamic link parameters. A many sorted fi…

cs.NI2020

Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches

Jorge López, Maxime Labonne, Claude Poletti +1

This paper proposes a novel admission and routing scheme which takes into account arbitrarily assigned priorities for network flows. The presented approach leverages the centralize…