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Adaptive Genetic Algorithm with Optimized Operators for Scheduling in Computer Systems Научная публикация

Конференция Intelligent Information Processing XII
03-06 мая 2024 , Shenzhen
Сборник Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings
Сборник, Springer. 2024. 505 c. ISBN 978-3-031-57808-3.
Журнал IFIP Advances in Information and Communication Technology
ISSN: 1868-4238 , E-ISSN: 1868-422X
Вых. Данные Год: 2024, Том: Part 1, Страницы: 317-328 Страниц : 12 DOI: 10.1007/978-3-031-57808-3_23
Ключевые слова Energy, Genetic algorithm, Parallelizable job, Scheduling, Speed scaling
Авторы Zakharova Yu.V. 1 , Sakhno M.Yu. 1
Организации
1 Sobolev Institute of Mathematics SB RAS, Omsk, Russia

Информация о финансировании (1)

1 Российский научный фонд 22-71-10015

Реферат: Modern computing and networking environments provide the important problems of efficient using such resources as energy and cores or processors. It is based on the possibility of dynamically varying the speed of processors and using parallel calculations in the execution of operations. We consider the NP-hard speed scaling scheduling problem with energy constraints and parallelizable jobs. Each job must be executed on the given number of processors. Processors can vary their speeds dynamically. It is required to assign speeds to jobs and schedule them such that the total completion time is minimized under the given energy budget. An adaptive genetic algorithm with optimized crossover operators is proposed. The optimal recombination problem is solved in the crossover operator. This problem is aimed at searching for the best possible offspring following the well-known gene transmitting property. The experimental evaluation shows that the algorithm outperforms the known metaheuristics and demonstrates the perspectives of using adaptive techniques and optimized operators.
Библиографическая ссылка: Zakharova Y.V. , Sakhno M.Y.
Adaptive Genetic Algorithm with Optimized Operators for Scheduling in Computer Systems
В сборнике Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings. – Springer., 2024. – Т.Part I. – C.317-328. – ISBN 978-3-031-57808-3. DOI: 10.1007/978-3-031-57808-3_23 Scopus OpenAlex
Даты:
Опубликована в печати: 6 апр. 2024 г.
Опубликована online: 6 апр. 2024 г.
Идентификаторы БД:
Scopus: 2-s2.0-85190657685
OpenAlex: W4393977319
Цитирование в БД:
БД Цитирований
Scopus 1
Альметрики: