A hybrid ant-genetic algorithm to solve a real deployment problem: a case study with experimental validation

Sami Mnasri (1) , Nejah Nasri (2) , Adrien van den Bossche (1, 3) , Thierry Val (1, 3)

1 IRIT-RMESS - Réseaux, Mobiles, Embarqués, Sans fil, Satellites
2 LETI - Laboratoire d'électronique et des technologies de l'Information [Sfax]
3 UT2J - Université Toulouse - Jean Jaurès

In this paper, we investigate the problem of deploying 3D nodes in a wireless sensor network. The aim is to choose the ideal 3D locations to add new nodes to an initial configuration of nodes, while optimizing a set of objectives. In this regard, our study proposes a new hybrid algorithm which stems from the ant foraging behavior and the genetics. It is based on a recent variant of the genetic algorithms (NSGA-III) and the Ant Colony Optimization algorithm. The obtained numerical results and the simulations compared with experiments prove the effectiveness of the proposed approach.

Mots clés: NSGA-III; ACO; Testbed; Prototyping; 3D indoor redeployment; DL-IoT

Domaines: Réseaux et télécommunications [cs.NI]; Système d'exploitation [cs.OS]; Architectures Matérielles [cs.AR]; Systèmes embarqués

Sami Mnasri, Nejah Nasri, Adrien van den Bossche, Thierry Val. A hybrid ant-genetic algorithm to solve a real deployment problem: a case study with experimental validation. International Conference on Ad Hoc Networks and Wireless (AdHoc-Now 2017), Sep 2017, Messina, Italy. pp. 367-381. ⟨hal-01913676⟩