This paper presents a design tool for WSNs based to optimization mecha- nisms that enable the user to build a network topology selected by optimizing different potential configurations. Through the suggested mechanisms, it can also be determined the optimal number of active network nodes to meet the requirements of a specific ap- plication before the physical implementation of the system. In this paper we propose a customizable heuristic approach of WSNs topology design based on genetic algorithms, in order to take account of specific application parameters: coverage, energy efficiency, system node degree in the environment and network lifetime. Innovation of our method is in a proper representation of different weight coefficients used to study the optimization of the network. The results of simulations prove that the overall network performance of the proposed heuristic deployment approach is superior compared to random WSN de- ployment.

Customizable hierarchical wireless sensor networks based on genetic algorithm / Zanaj, Elma; Gambi, Ennio; Zanaj, Blerina; Disha, Deivis. - In: INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING, INFORMATION & CONTROL. - ISSN 1349-4198. - ELETTRONICO. - 16:5(2020), pp. 1623-1638. [10.24507/ijicic.16.05.1623]

Customizable hierarchical wireless sensor networks based on genetic algorithm

Ennio Gambi;Deivis Disha
2020-01-01

Abstract

This paper presents a design tool for WSNs based to optimization mecha- nisms that enable the user to build a network topology selected by optimizing different potential configurations. Through the suggested mechanisms, it can also be determined the optimal number of active network nodes to meet the requirements of a specific ap- plication before the physical implementation of the system. In this paper we propose a customizable heuristic approach of WSNs topology design based on genetic algorithms, in order to take account of specific application parameters: coverage, energy efficiency, system node degree in the environment and network lifetime. Innovation of our method is in a proper representation of different weight coefficients used to study the optimization of the network. The results of simulations prove that the overall network performance of the proposed heuristic deployment approach is superior compared to random WSN de- ployment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/282959
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