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. ( 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019 deu 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.
2019
Inglese
22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019
deu
2019
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11454
430
438
9783030166915
9783030166922
Springer Verlag
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
5G; Matheuristic; Robust Optimization; Traffic uncertainty; Virtual Network Function
Goal 9: Industry, Innovation, and Infrastructure
Bauschert, T.; D'Andreagiovanni, F.; Kassler, A.; Wang, C.
Atti di CONVEGNO::Relazione in Atti di Convegno
273
4
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. ( 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019 deu 2019) [10.1007/978-3-030-16692-2_29].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1388998
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