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Inference of a clear channel assessment based conflict graph
Author(s) -
Abdelwedoud Lafdal,
Busson Anthony,
GuérinLassous Isabelle,
Foare Marion,
Diakité Mohamed L.,
Nanne Mohamedade F.
Publication year - 2020
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.227
Subject(s) - computer science , graph , inference , markov chain , controller (irrigation) , enhanced data rates for gsm evolution , set (abstract data type) , channel (broadcasting) , computer network , distributed computing , data mining , theoretical computer science , artificial intelligence , machine learning , agronomy , biology , programming language
We consider an IEEE 802.11 network composed of several Access Points (APs) managed by one controller. The controller relies on pieces of information describing the network state as channels, load, associated stations, conflicts, etc. to configure and optimize the network. In this paper, we propose a method that infers the way the different channels are shared between APs according to the Clear Channel Assessment (CCA) mechanism. It is represented through a conflict graph where an edge exists if two APs are able to detect each other. As this detection is sometimes partial, the links are weighted. Our method relies on measures already available on most of Wi‐Fi products and does not generate any traffic except the transmission of these measures to the controller. A Markov network and an optimization problem are then proposed to infer the weights of the conflict graph. Our solution is shown accurate on a large set of simulations performed with the network simulator ns‐3.