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QoS routing in cluster OLSR by using the artificial intelligence model MSSP in the big data environnment

Oubaha, JawadLakki, NoureddineOuacha, Ali
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 Juni 2021
DOI10.11591/ijai.v10.i2.pp458-466

Abstrak

The most complex problems, in data science and more specifically in artificial intelligence, can be modeled as cases of the maximum stable set problem (MSSP). this article describes a new approach to solve the MSSP problem by proposing the continuous hopfield network (CHN) to build optimized link state protocol routing (OLSR) protocol cluster. our approach consists in proposing in two stages: the first acts at the level of the choice of the OLSR master cluster in order to quickly make a local minimum using the CHN, by modeling the MSSP problem. As for the second step, the objective is the improvement of the precision making a solution of efficient at the first rank of neighborhood as a linear constraint, and at the end, to find the resolution of the model using the CHN. We will show that this model determines a good solution of the MSSP problem. To test the theoretical results, we propose a comparison with a classic OLSR.

Kata Kunci

Big DataMANETMSSPOLSRQuality of ServiceRouting

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QoS routing in cluster OLSR by using the artificial intelligence model MSSP in the big data environnment | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora