QGAC: Quantum Genetic Based-Clustering Algorithm for WSNs
Djamila Mechta, Saad Harous · 2018
In this paper, we present a novel approach for clustering based on quantum genetic computing and complex systems. The main idea is the use of Wireless Sensor Networks (WSNs) as complex system, and Quantum Computing algorithms (QC) as research strategy. WSNs are a set of sensors that operate in parallel and interact with their neighbors using single hop or multi-hops communication. The problem with WSNs is to find, within a large set of sensors randomly deployed, the subset of best clusters and their Cluster Heads (CHs) and ensure their balanced distribution in network. To cope with this NP-hard problem, we propose a new Quantum Genetic Clustering Algorithm (QGCA) which is based on Quantum Genetic Algorithm (QGA) for CHs selection to reduce energy consumption and extend the network lifetime. A comparison is made between classical routing protocol LEACH and the proposed QGCA. Experiments show that the efficiency of QGCA is significantly better and clearly indicate that the proposed approach outperforms random CHs selection and leads to significant increase in network lifetime.