TY - JOUR
AU - Taiwe, Kolyang Dina
AB - To achieve important properties of wireless mesh networks (WMNs) such as coverage and reliability, the placement of mesh nodes plays an important role. The impact of the mesh node placement on the performance of WMNs has been carried out in the past years. To improve such properties, we propose a novel scheme for mesh node placement in WMNs. We have developed a multi-objective optimisation model for node placement where the coverage, reliability and the total installation cost in terms of nodes to be deployed are the three objectives to optimise simultaneously. We first applied the two well-known evolutionary algorithms, namely the non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective genetic algorithm (MOGA) to generate the number and positions of the communication nodes. Subsequently, we developed algorithms that determine the cluster formation, gateway selection and relay nodes selection. The results showed satisfactory performance.
TI - Mesh node placement in wireless mesh network based on multiobjective evolutionary metaheuristic
JF - International Journal of Autonomic Computing
DO - 10.1504/IJAC.2017.086981
DA - 2017-01-01
UR - https://www.deepdyve.com/lp/inderscience-publishers/mesh-node-placement-in-wireless-mesh-network-based-on-multiobjective-DpPEaUGIWz
SP - 231
EP - 254
VL - 2
IS - 3
DP - DeepDyve
ER -