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QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm

Service function chaining (SFC) is a mechanism that allows service providers to combine various service functions and exploit the available virtual infrastructure. The best selection of virtual services in the network is essential for meeting user requirements and constraints. This paper proposes a...

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Autores principales: Khosravian, Pouya, Emadi, Sima, Mirjalily, Ghasem, Zamani, Behzad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323722/
https://www.ncbi.nlm.nih.gov/pubmed/34395858
http://dx.doi.org/10.7717/peerj-cs.603
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author Khosravian, Pouya
Emadi, Sima
Mirjalily, Ghasem
Zamani, Behzad
author_facet Khosravian, Pouya
Emadi, Sima
Mirjalily, Ghasem
Zamani, Behzad
author_sort Khosravian, Pouya
collection PubMed
description Service function chaining (SFC) is a mechanism that allows service providers to combine various service functions and exploit the available virtual infrastructure. The best selection of virtual services in the network is essential for meeting user requirements and constraints. This paper proposes a novel approach to generate the optimal composition of the service functions. To this end, a genetic algorithm based on context-free grammar (CFG) that adheres to the Internet Engineering Task Force (IETF) standard and Skyline was developed to use in SFC. The IETF uses cases of the data center, security, and mobile network filtered out the invalid service chains, which resulted in reduced search space. The proposed genetic algorithm found the Skyline service chain instance with the highest quality. The genetic operations were defined to ensure that the service function chains generated in the algorithm process were standard. The experimental results showed that the proposed service composition method outperformed the other methods regarding the quality of service (QoS), running time, and time complexity metrics. Ultimately, the proposed CFG could be generalized to other SFC use cases.
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spelling pubmed-83237222021-08-13 QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm Khosravian, Pouya Emadi, Sima Mirjalily, Ghasem Zamani, Behzad PeerJ Comput Sci Artificial Intelligence Service function chaining (SFC) is a mechanism that allows service providers to combine various service functions and exploit the available virtual infrastructure. The best selection of virtual services in the network is essential for meeting user requirements and constraints. This paper proposes a novel approach to generate the optimal composition of the service functions. To this end, a genetic algorithm based on context-free grammar (CFG) that adheres to the Internet Engineering Task Force (IETF) standard and Skyline was developed to use in SFC. The IETF uses cases of the data center, security, and mobile network filtered out the invalid service chains, which resulted in reduced search space. The proposed genetic algorithm found the Skyline service chain instance with the highest quality. The genetic operations were defined to ensure that the service function chains generated in the algorithm process were standard. The experimental results showed that the proposed service composition method outperformed the other methods regarding the quality of service (QoS), running time, and time complexity metrics. Ultimately, the proposed CFG could be generalized to other SFC use cases. PeerJ Inc. 2021-07-26 /pmc/articles/PMC8323722/ /pubmed/34395858 http://dx.doi.org/10.7717/peerj-cs.603 Text en © 2021 Khosravian et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Artificial Intelligence
Khosravian, Pouya
Emadi, Sima
Mirjalily, Ghasem
Zamani, Behzad
QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title_full QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title_fullStr QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title_full_unstemmed QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title_short QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
title_sort qos-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323722/
https://www.ncbi.nlm.nih.gov/pubmed/34395858
http://dx.doi.org/10.7717/peerj-cs.603
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