arXiv subjects

Ivan Marsa-Maestre

Publications and source records attributed to Ivan Marsa-Maestre.

4 recordsLinked to original sources

arXiv2019

REACT: REActive resilience for critical infrastructures using graph-Coloring Techniques

Nowadays society is more and more dependent on critical infrastructures. Critical network infrastructures (CNI) are communication networks whose disruption can create a severe impact. In this paper we propose REACT, a distributed framework for reactive network resilience, which allows networks to reconfigure themselves in the event of a security incidents so that the risk of further damage is mitigated. Our framework takes advantage of a risk model based on multilayer networks, as well as a graph-coloring problem conversion, to identify new, more resilient configurations for networks in the event of an attack. We propose two different solution approaches, and evaluate them from two different perspectives, with a number of centralized optimization techniques. Experiments show that our approaches outperform the reference approaches in terms of risk mitigation and performance.

cs.NI↗

arXiv2019

Nonlinear Negotiation Approaches for Complex-Network Optimization: A Study Inspired by Wi-Fi Channel Assignment

At the present time, Wi-Fi networks are everywhere. They operate in unlicensed radio-frequency spectrum bands (divided in channels), which are highly congested. The purpose of this paper is to tackle the problem of channel assignment in Wi-Fi networks. To this end, we have modeled the networks as multilayer graphs, in a way that frequency channel assignment becomes a graph coloring problem. For a high number and variety of scenarios, we have solved the problem with two different automated negotiation techniques: a hill-climber and a simulated annealer. As an upper bound reference for the performance of these two techniques, we have also solved the problem using a particle swarm optimizer. Results show that the annealer negotiator behaves as the best choice because it is able to obtain even better results than the particle swarm optimizer in the most complex scenarios under study, with running times one order of magnitude below. Finally, we study how different properties of the network layout affect to the performance gain that the annealer is able to obtain with respect to the particle swarm optimizer.

cs.NI↗

arXiv2018

Spectrum graph coloring to improve Wi-Fi channel assignment in a real-world scenario via edge contraction

The present work deals with the problem of efficiently assigning Wi-Fi channels in a real-world scenario, the Polytechnic School of the University of Alcalá. We first use proximity graphs to model the whole problem as an instance of spectrum graph coloring, we further obtain a simplified model using edge contraction, and we finally use simulated annealing to look for a coloring which optimizes the network throughput. As the main result, we show that the solutions we obtain outperform the de facto standard for Wi-Fi channel assignment, both in terms of network throughput and of computation time.

cs.DM↗

arXiv2017

Spectrum graph coloring and applications to WiFi channel assignment

We introduce and explore a family of vertex-coloring problems which, surprisingly enough, have not been considered before despite stemming from the problem of Wi-Fi channel assignment. Given a spectrum of colors, endowed with a matrix of interferences between each pair of colors, the Threshold Spectrum Coloring problem fixes the number of colors available and aims to minimize the interference threshold, i.e., the maximum of the interferences at the vertices. Conversely, the Chromatic Spectrum Coloring problem fixes a threshold and aims to minimize the number of colors for which respecting that threshold is possible. As main theoretical results, we prove tight upper bounds for the solutions to each problem. Since both problems turn out to be NP-hard, we complete the scene with experimental results. We propose a DSATUR-based heuristic and study its performance to minimize the maximum vertex interference in Wi-Fi channel assignment, both for randomly generated graphs and for a real-world scenario. Further, for all these graphs we experimentally check the goodness of the theoretical bounds.

cs.DM↗