Abstract
5G Networks are strongly dependent on software-based management and processing. Services offered inside this environment are composed of several Virtual Network Functions (VNFs) that must be executed in a (normally) strict order. This is known as Service Function Chaining (SFC) and, given that those VNFs could be placed in different nodes along the network together with the expected low latency in the processing of 5G services, makes SFC a tough optimization problem. In a previous work, the authors presented an Ant Colony Optimization (ACO) algorithm for the minimization of the routing cost of service chain composition, but it was a preliminary approach able to solve simple and ‘static’ instances (i.e. network topology is invariable). Thus, in this work we describe an evolution of our previous proposal, which consider a dynamic model of the problem, closer to the real scenario. So, in the instances nodes and links can be removed suddenly or, on the contrary, they could arise. The ACO algorithm will be able to adapt to these changes and still yield optimal solutions. The Adaptive Ant-SFC method has been tested in three dynamic instances with different sizes, obtaining very promising results.
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Acknowledgements
This work has been partially funded by projects RTI2018-102002-A-I00 (Ministerio de Ciencia, Innovación y Universidades), TIN2017-85727-C4-2-P (Ministerio de Economía y Competitividad), B-TIC-402-UGR18 (FEDER and Junta de Andalucía), and project P18-RT-4830 (Junta de Andalucía).
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Moreno, S., Mora, A.M. (2021). Adaptive Ant Colony Optimization for Service Function Chaining in a Dynamic 5G Network. In: Rojas, I., Joya, G., Català, A. (eds) Advances in Computational Intelligence. IWANN 2021. Lecture Notes in Computer Science(), vol 12861. Springer, Cham. https://doi.org/10.1007/978-3-030-85030-2_13
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DOI: https://doi.org/10.1007/978-3-030-85030-2_13
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