We investigate the problem of optimally placing virtual network functions in 5G-based virtualized infrastructures according to a green paradigm that pursues energy-efficiency. This optimization problem can be modelled as an articulated 0-1 Linear Program based on a flow model. Since the problem can prove hard to be solved by a state-of-the-art optimization software, even for instances of moderate size, we propose a new fast matheuristic for its solution. Preliminary computational tests on a set of realistic instances return encouraging results, showing that our algorithm can find better solutions in considerably less time than a state-of-the-art solver.
A matheuristic for green and robust 5G virtual network function placement / Bauschert, T.; D'Andreagiovanni, F.; Kassler, A.; Wang, C.. - 11454:(2019), pp. 430-438. (Intervento presentato al convegno 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019 tenutosi a deu nel 2019) [10.1007/978-3-030-16692-2_29].
A matheuristic for green and robust 5G virtual network function placement
D'Andreagiovanni F.
;
2019
Abstract
We investigate the problem of optimally placing virtual network functions in 5G-based virtualized infrastructures according to a green paradigm that pursues energy-efficiency. This optimization problem can be modelled as an articulated 0-1 Linear Program based on a flow model. Since the problem can prove hard to be solved by a state-of-the-art optimization software, even for instances of moderate size, we propose a new fast matheuristic for its solution. Preliminary computational tests on a set of realistic instances return encouraging results, showing that our algorithm can find better solutions in considerably less time than a state-of-the-art solver.| File | Dimensione | Formato | |
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