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Dynamic Pricing for Tenants in an Automated Slicing Marketplace

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Game Theory for Networks (GameNets 2022)

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Abstract

The paradigm shift from a one-size-fits-all architecture to a service-oriented network infrastructure promised by network slicing will demand novel technical solutions, as well as new business models. In particular, the role separation between infrastructure providers, i.e. the ones owning the network, and slice tenants, i.e. the ones providing specialized services tailored to their vertical segments, may encourage the definition of a shared platform (or marketplace) where the former can monetize their network infrastructure by leasing network resources at a market price, and the latter can rent on-demand the network resources needed to offer their services at the desired quality. This also enables the flexibility for the slice tenants to optimize the management of their slices by adapting their resource demand to fluctuations of their traffic or variations of the price in the market. In this paper, we extend the market mechanism scheme developed in previous works by including intra-slice radio admission control policies in the utility definition of the tenants in the slicing market game. Moreover, we characterize the mathematical properties of the game with respect to slice configuration, i.e. how diverse strategical behavior of the tenants affects the market operation, in terms of slice resource allocation and performance. Our analysis offers insights to the slice tenants on how they could reconfigure their techno-economic performance indicators in response to the dynamics of network and of the market, namely how to adapt their long-term (and/or real-time) strategies to the fluctuations of the traffic to enhance network performance and increase profits.

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Notes

  1. 1.

    This assumption holds for simplicity. In general, a single tenant may control multiple network slices and still have different business models for each of them.

  2. 2.

    In the rest of the work, we assume that the resources are evenly split among the users, i.e. \(x_k \simeq \frac{x_s}{|K_s|}\) - with \(|\cdot |\) denoting the cardinality of a set - as achieved by the state of the art proportional fair schedulers [4, 10].

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Authors and Affiliations

  1. Nokia Bell Labs, Stuttgart, Germany

    Alessandro Lieto, Ilaria Malanchini & Silvio Mandelli

  2. Politecnico di Milano, Milan, Italy

    Antonio Capone

Authors
  1. Alessandro Lieto
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  2. Ilaria Malanchini
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  3. Silvio Mandelli
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  4. Antonio Capone
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Corresponding author

Correspondence to Alessandro Lieto .

Editor information

Editors and Affiliations

  1. Western University, London, ON, Canada

    Fang Fang

  2. Chongqing University, Chongqing, China

    Fu Shu

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lieto, A., Malanchini, I., Mandelli, S., Capone, A. (2022). Dynamic Pricing for Tenants in an Automated Slicing Marketplace. In: Fang, F., Shu, F. (eds) Game Theory for Networks. GameNets 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 457. Springer, Cham. https://doi.org/10.1007/978-3-031-23141-4_21

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  • DOI: https://doi.org/10.1007/978-3-031-23141-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23140-7

  • Online ISBN: 978-3-031-23141-4

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