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

Abstract

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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“…(4) for higher values of . GA has been shown to be effective in solving a wide range of applications in science and engineering ( Khosravian et al, 2021 ; Zhang, 2019 ; Yang, Gomez & Blackburn, 2020 ; Katoch, Chauhan & Kumar, 2021 ; Velasco et al, 2020 ; Caro, Mendoza & Mendoza, 2021 ; Jamilla, Mendoza & Mendoza, 2021 ). For ease of use and open accessibility, the GA we implement is from the geneticalgorithm Python package, which has options for integer programming.…”