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Article

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Title

Assignment of tasks to machines under data replication with a tie to Steiner systems

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2024

Published in

International Journal of Applied Mathematics and Computer Science

Journal year: 2024 | Journal volume: vol. 34 | Journal number: no. 2

Article type

scientific article

Publication language

english

Keywords
EN
  • task assignment
  • genomic data processing
  • integer linear programming
  • Steiner system
  • heuristic algorithm
Abstract

EN In the paper a problem of assignment of tasks to machines is formulated and solved, where a criterion of data replication is used and a large size of data imposes additional constraints. This problem is met in practice when dealing with large genomic files or other types of vast data. The necessity of comparing all pairs of files within a big set of DNA sequencing results, which we collected, maintained, and analyzed within a national genomic project, brought us to the proposed results. This problem resembles that of generating a particular Steiner system, and a mechanism observed there is employed in one of our algorithms. Based on the problem complexity, we propose two heuristic algorithms, which work very well even for instances with tight constraints and a heterogeneous environment defined. In addition, we propose a simplified method, nevertheless capable of finding very good solutions and surpassing the algorithms in some special cases. The methods are validated in tests on a wide set of instances, where values of parameters reflect our real-world application and where their usefulness is proven.

Pages (from - to)

263 - 275

DOI

10.61822/amcs-2024-0019

URL

https://sciendo.com/pl/article/10.61822/amcs-2024-0019

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

100

Impact Factor

1,6 [List 2023]

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