TY - GEN
T1 - Multi-Tier Topology Design of Wireless Sensor Networks using Multi-Objective Particle Swarm Optimization
AU - Amron, Kasyful
AU - Kusumawinahyu, Wuryansari Muharini
AU - Anam, Syaiful
AU - Mahmudy, Wayan Firdaus
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/11/22
Y1 - 2022/11/22
N2 - In WSN, node placement is the most fundamental and growing topic since the location and function of the nodes define network performance. Recently, the placement methods are formulated as an optimization problem and solved by multi-objective optimization (MOO) approaches. This research aims to examine the implementation of MOO for relay placement. The goals of the MOO are to develop a WSN with minimum cost and fault tolerance ability. The MOO method in this research was constructed over a swarm intelligence algorithm. The area with targets and sensors is mapped into triangular cells and relays are placed at the triangular points. This mapping allows each sensor to connect to at least two different relays and construct multi-paths to the sink with the minimum number of relays. With random sensors that cover the entire area, this method uses around 58% to 67% of all relays on average.
AB - In WSN, node placement is the most fundamental and growing topic since the location and function of the nodes define network performance. Recently, the placement methods are formulated as an optimization problem and solved by multi-objective optimization (MOO) approaches. This research aims to examine the implementation of MOO for relay placement. The goals of the MOO are to develop a WSN with minimum cost and fault tolerance ability. The MOO method in this research was constructed over a swarm intelligence algorithm. The area with targets and sensors is mapped into triangular cells and relays are placed at the triangular points. This mapping allows each sensor to connect to at least two different relays and construct multi-paths to the sink with the minimum number of relays. With random sensors that cover the entire area, this method uses around 58% to 67% of all relays on average.
KW - Fault-Tolerant
KW - Minimum Cost
KW - Multi-Objective Optimization
KW - Particle Swarm Optimization
KW - Relay Nodes Placement
KW - Wireless Sensor Networks
UR - https://www.scopus.com/pages/publications/85146951492
U2 - 10.1145/3568231.3568255
DO - 10.1145/3568231.3568255
M3 - Conference contribution
AN - SCOPUS:85146951492
T3 - ACM International Conference Proceeding Series
SP - 103
EP - 110
BT - SIET 2022 - Proceedings of 7th International Conference on Sustainable Information Engineering and Technology 2022
PB - Association for Computing Machinery
T2 - 7th International Conference on Sustainable Information Engineering and Technology, SIET 2022
Y2 - 22 November 2022
ER -