TY  - CONF
AV  - none
EP  - 169
TI  - Optimal Node Placement and Congestion Reduction in an Industrial Wireless Mesh Network using HHO Algorithm
KW  - MESH networking; Network topology; Particle swarm optimization (PSO); Traffic congestion; Wireless mesh networks (WMN)
KW  -  Harris hawk optimization; Industrial control systems; MeshNetworks; Meta-heuristics algorithms; Optimisations; Particle swarm; Particle swarm optimization; Swarm optimization; Wireless mesh; Wireless mesh network
KW  -  Mesh generation
N1  - cited By 3; Conference of 2022 International Conference on Future Trends in Smart Communities, ICFTSC 2022 ; Conference Date: 1 December 2022 Through 2 December 2022; Conference Code:186671
SN  - 9798350334548
ID  - scholars17258
Y1  - 2022///
A1  - Abdulrab, H.
A1  - Hussin, F.A.
A1  - Awang, A.
A1  - Ismail, I.
A1  - Devan, P.A.M.
A1  - Shutari, H.
PB  - Institute of Electrical and Electronics Engineers Inc.
SP  - 164
N2  - When it comes to improving the performance of a wireless mesh network, the positioning of routers is critical. In order to provide the greatest network accessibility, it is essential that mesh routers be installed in appropriate locations. One way to improve the network's performance is to increase the coverage while utilizing an optimum number of routers. The network coverage may be optimised using a number of different techniques that have been developed over time in the scientific literature. An algorithm called Harris Hawk's Optimization (HHO) is being used in this study to optimally locate mesh routers in a mesh network in order to optimise coverage and reduce network congestion. The HHO identifies the best positions to place the routers in order to have the best possible network topology by removing the overlapping routers to minimize the number of routers while keeping the coverage maximized. In this research, 60, and 100 mesh routers are deployed in two different network topologies. The simulation results are analysed and compared with Sine Cosine Algorithm (SCA), Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithm. With regard to network coverage and congestion reduction, simulation results show that HHO surpasses the benchmark algorithms by having 98 coverage and 34 reduction in the network size. © 2022 IEEE.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149115086&doi=10.1109%2fICFTSC57269.2022.10039952&partnerID=40&md5=a83d59ed73fae5e9e21009e8e69ebeb9
ER  -