A matheuristic for green and robust 5G virtual network function placement
2019 (English)In: Applications of Evolutionary Computation / [ed] Paul Kaufmann, Pedro A. Castillo, Cham: Springer, 2019, p. 430-438Conference paper, Published paper (Refereed)
Abstract [en]
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.
Place, publisher, year, edition, pages
Cham: Springer, 2019. p. 430-438
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11454
Keywords [en]
5G, Matheuristic, Robust Optimization, Traffic uncertainty, Virtual Network Function, 5G mobile communication systems, Energy efficiency, Linear programming, Transfer functions, Computational tests, Optimization problems, Optimization software, State of the art, Traffic uncertainties, Virtual networks, Network function virtualization
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-72518DOI: 10.1007/978-3-030-16692-2_29Scopus ID: 2-s2.0-85065708641ISBN: 978-3-030-16691-5 (print)ISBN: 978-3-030-16692-2 (electronic)OAI: oai:DiVA.org:kau-72518DiVA, id: diva2:1324212
Conference
22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019
2019-06-132019-06-132019-11-11Bibliographically approved