TY - GEN
T1 - Relay nodes placement for optimal coverage, connectivity, and communication of wireless sensor networks
T2 - 5th International Conference on Sustainable Information Engineering and Technology, SIET 2020
AU - Amron, Kasyful
AU - Kusumawinahyu, Wuryansari M.
AU - Anam, Syaiful
AU - Mahmudy, Wayan F.
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/16
Y1 - 2020/11/16
N2 - Designing a Wireless Sensor Networks (WSN) mostly was a great challenge. Shown in previous results, some design approaches lead to problems in its implementation. Deterministic methods face the NP-Hard complex problem. On the other side, heuristic methods sometimes produce a flawed result. With those situations, this research concern with exploring the possibility of a multi-objective optimization (MOO) method. As with the MOO method, some conflicted WSN aspects consider simultaneously. Started with the PSO algorithm, this developing method tries to find the best position of the WSN's relays. Closed neighbor sensor nodes are then will be connected. It is combined with the graph to constructs the best communication link. These steps will be done in a certain number of iterations to enhance fault-tolerance ability. This MOO approached method was implemented to different WSN topologies, with several sensors placed in a simulation area. Used as controls are Steiner Point and Triangular Grid algorithms. The most significant finding is this developing method gave some early potential results that could form future solutions in the multi-objective optimization approach for the WSN designing.
AB - Designing a Wireless Sensor Networks (WSN) mostly was a great challenge. Shown in previous results, some design approaches lead to problems in its implementation. Deterministic methods face the NP-Hard complex problem. On the other side, heuristic methods sometimes produce a flawed result. With those situations, this research concern with exploring the possibility of a multi-objective optimization (MOO) method. As with the MOO method, some conflicted WSN aspects consider simultaneously. Started with the PSO algorithm, this developing method tries to find the best position of the WSN's relays. Closed neighbor sensor nodes are then will be connected. It is combined with the graph to constructs the best communication link. These steps will be done in a certain number of iterations to enhance fault-tolerance ability. This MOO approached method was implemented to different WSN topologies, with several sensors placed in a simulation area. Used as controls are Steiner Point and Triangular Grid algorithms. The most significant finding is this developing method gave some early potential results that could form future solutions in the multi-objective optimization approach for the WSN designing.
KW - communication path
KW - fault-tolerant
KW - minimum cost
KW - multi-objective optimization
KW - particle swarm optimization
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/85099021492
U2 - 10.1145/3427423.3427452
DO - 10.1145/3427423.3427452
M3 - Conference contribution
AN - SCOPUS:85099021492
T3 - ACM International Conference Proceeding Series
SP - 177
EP - 182
BT - Proceedings of 2020 International Conference on Sustainable Information Engineering and Technology, SIET 2020
PB - Association for Computing Machinery
Y2 - 16 November 2020 through 17 November 2020
ER -