Parallel Genetic Algorithm for Sink Nodes Placement to Maximize Network Reliability

Aleksandr Tarasov, Denis Migov

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

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.

Язык оригиналаанглийский
Название основной публикацииProceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы126-129
Число страниц4
ISBN (электронное издание)978-1-6654-0562-1
DOI
СостояниеОпубликовано - 2021
Событие17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021 - Moscow, Российская Федерация
Продолжительность: 13 сен 202117 сен 2021

Серия публикаций

НазваниеProceedings - 2021 17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021

Конференция

Конференция17th International Asian School-Seminar "Optimization Problems of Complex Systems", OPCS 2021
СтранаРоссийская Федерация
ГородMoscow
Период13.09.202117.09.2021

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