1 code implementation • 18 Sep 2023 • Alessandro Finamore, Chao Wang, Jonatan Krolikowski, Jose M. Navarro, Fuxing Chen, Dario Rossi
Over the last years we witnessed a renewed interest toward Traffic Classification (TC) captivated by the rise of Deep Learning (DL).
no code implementations • 21 Feb 2023 • Jonatan Krolikowski, Zied Ben Houidi, Dario Rossi
Yet each network comes with its unique distribution of users in space, calling for a power control that adapts to users' probabilities of presence, for example, placing the areas with higher interference probabilities where user density is the lowest.
no code implementations • 25 Nov 2022 • Danilo Marinho Fernandes, Jonatan Krolikowski, Zied Ben Houidi, Fuxing Chen, Dario Rossi
Airtime interference is a key performance indicator for WLANs, measuring, for a given time period, the percentage of time during which a node is forced to wait for other transmissions before to transmitting or receiving.
no code implementations • 3 Jan 2022 • Matteo Boffa, Zied Ben Houidi, Jonatan Krolikowski, Dario Rossi
Recent years have witnessed the promise that reinforcement learning, coupled with Graph Neural Network (GNN) architectures, could learn to solve hard combinatorial optimization problems: given raw input data and an evaluator to guide the process, the idea is to automatically learn a policy able to return feasible and high-quality outputs.
no code implementations • 22 Apr 2017 • Fabio D'Andreagiovanni, Jonatan Krolikowski, Jonad Pulaj
Given the intrinsic difficulty of the problem, which proves challenging even for state-of-the art commercial solvers, we propose a hybrid primal heuristic based on the combination of ant colony optimization and an exact large neighborhood search.
no code implementations • 21 Oct 2014 • Fabio D'Andreagiovanni, Jonatan Krolikowski, Jonad Pulaj
We investigate the Robust Multiperiod Network Design Problem, a generalization of the Capacitated Network Design Problem (CNDP) that, besides establishing flow routing and network capacity installation as in a canonical CNDP, also considers a planning horizon made up of multiple time periods and protection against fluctuations in traffic volumes.