No-Regret Slice Reservation Algorithms

Jean-Baptiste Monteil, George Iosifidis, Luiz DaSilva

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
10 Downloads (Pure)


Emerging network slicing markets promise to boost the utilization of expensive network resources and to unleash the potential of over-the-top services. Their success, however, is conditioned on the service providers (SPs) being able to bid effectively for the virtualized resources. In this paper we consider a hybrid advance-reservation and spot slice market and study how the SPs should reserve slices in order to maximize their performance while not exceeding their budget. We consider this problem in its general form, where the SP demand and slice prices are time-varying and revealed only after the reservations are decided. We develop a learning-based framework, using the theory of online convex optimization, that allows the SP to employ a no-regret reservation policy, i.e., achieve the same performance with a hypothetical policy that has knowledge of future demand and prices. We extend our framework for the scenario the SP decides dynamically its slice orchestration, where it additionally needs to learn which resource composition is performance - maximizing; and we propose a mixed-time scale scheme that allows the SP to leverage any spot-market information revealed between its reservations. We evaluate our learning framework and its extensions using a variety of simulation scenarios and following a detailed parameter sensitivity analysis.
Original languageEnglish
Title of host publicationICC 2021 - IEEE International Conference on Communications
Subtitle of host publicationProceedings
Place of PublicationPiscataway
Number of pages7
ISBN (Electronic)978-1-7281-7122-7
ISBN (Print)978-1-7281-7123-4
Publication statusPublished - 2021
EventICC 2021 - IEEE International Conference on Communications - Virtual at Montreal, Canada
Duration: 14 Jun 202123 Jun 2021


ConferenceICC 2021 - IEEE International Conference on Communications
CityVirtual at Montreal

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Online convex optimization
  • network slicing markets
  • virtualization
  • resource reservation
  • SP utility maximization
  • constrained optimization
  • duality


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