Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Parallel Genetic Algorithm for Sink Nodes Placement to Maximize Network Reliability. / Tarasov, Aleksandr; Migov, Denis.
Proceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. стр. 126-129 (Proceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Parallel Genetic Algorithm for Sink Nodes Placement to Maximize Network Reliability
AU - Tarasov, Aleksandr
AU - Migov, Denis
N1 - Funding Information: The reported study was funded by RFBR and NSFC, project number 21-57-53011. Publisher Copyright: © 2021 IEEE
PY - 2021
Y1 - 2021
N2 - A parallel genetic algorithm for optimizing the location of sink nodes of a wireless sensor network is proposed. As an optimization criterion we consider a reliability of a wireless sensor network under the assumption that nodes of a wireless sensor network are subject of random independent failures due to scuffing, intrusions, or other reasons. As a result, some sensors can become disconnected from sink nodes that collect data from all the sensors. A random graph with unreliable nodes and absolutely reliable edges is used as a model of such wireless sensor networks. By wireless sensor network reliability we mean the mathematical expectation of the number of sensors connected to any sink node (MENC). For reliability calculation a well-known factoring method is used. Various optimization algorithms are considered: a canonical genetic algorithm, a module genetic algorithm, an island genetic algorithm, and an island genetic algorithm with migration. The results of the numerical experiments are given.
AB - A parallel genetic algorithm for optimizing the location of sink nodes of a wireless sensor network is proposed. As an optimization criterion we consider a reliability of a wireless sensor network under the assumption that nodes of a wireless sensor network are subject of random independent failures due to scuffing, intrusions, or other reasons. As a result, some sensors can become disconnected from sink nodes that collect data from all the sensors. A random graph with unreliable nodes and absolutely reliable edges is used as a model of such wireless sensor networks. By wireless sensor network reliability we mean the mathematical expectation of the number of sensors connected to any sink node (MENC). For reliability calculation a well-known factoring method is used. Various optimization algorithms are considered: a canonical genetic algorithm, a module genetic algorithm, an island genetic algorithm, and an island genetic algorithm with migration. The results of the numerical experiments are given.
KW - factorization method
KW - genetic algorithm
KW - Network optimization
KW - network reliability
KW - parallel algorithm
KW - random graph
KW - wireless sensor network
UR - http://www.scopus.com/inward/record.url?scp=85126909946&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/9572198a-e001-36b6-a160-c75d331d5c37/
U2 - 10.1109/OPCS53376.2021.9588716
DO - 10.1109/OPCS53376.2021.9588716
M3 - Conference contribution
AN - SCOPUS:85126909946
SN - 9781665405621
T3 - Proceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021
SP - 126
EP - 129
BT - Proceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021
Y2 - 13 September 2021 through 17 September 2021
ER -
ID: 35770575