Strategic Resource Pricing and Allocation ...
Type de document :
Pré-publication ou Document de travail
Titre :
Strategic Resource Pricing and Allocation in a 5G Network Slicing Stackelberg Game
Auteur(s) :
Datar, Mandar [Auteur]
Laboratoire Informatique d'Avignon [LIA]
Network Engineering and Operations [NEO ]
Altman, Eitan [Auteur]
Laboratory of Information, Network and Communication Sciences [LINCS]
Laboratoire Informatique d'Avignon [LIA]
Network Engineering and Operations [NEO ]
Le Cadre, Hélène [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Integrated Optimization with Complex Structure [INOCS]
Laboratoire Informatique d'Avignon [LIA]
Network Engineering and Operations [NEO ]
Altman, Eitan [Auteur]
Laboratory of Information, Network and Communication Sciences [LINCS]
Laboratoire Informatique d'Avignon [LIA]
Network Engineering and Operations [NEO ]
Le Cadre, Hélène [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Integrated Optimization with Complex Structure [INOCS]
Mot(s)-clé(s) en anglais :
Communication service market
game theory
trading post mechanism
pricing
5G network slicing
resource allocation
game theory
trading post mechanism
pricing
5G network slicing
resource allocation
Discipline(s) HAL :
Informatique [cs]
Sciences de l'ingénieur [physics]
Mathématiques [math]
Sciences de l'ingénieur [physics]
Mathématiques [math]
Résumé en anglais : [en]
We consider a marketplace in the context of 5G network slicing, where service providers (SP), i.e., slice tenants, are in competition for the access to the network resource owned by an infrastructure provider who relies ...
Lire la suite >We consider a marketplace in the context of 5G network slicing, where service providers (SP), i.e., slice tenants, are in competition for the access to the network resource owned by an infrastructure provider who relies on network slicing. We model the interactions between the end-users (followers) and the SPs (leaders) as a Stackelberg game. We prove that the competition between the SPs results in a multi-resource Tullock rent-seeking game. To determine resource pricing and allocation, we devise two innovative market mechanisms. First, we assume that the SPs are pre-assigned with fixed shares (budgets) of infrastructure, and rely on a trading post mechanism to allocate the resource. Under this mechanism, the SPs can redistribute their budgets in bids and customise their allocations to maximise their profits. We prove that their decision problems give rise to a noncooperative game, which admits a unique Nash equilibrium when dealing with a single resource. Second, when SPs have no bound on their budget, we formulate the problem as a pricing game with coupling constraints and derive the market prices as the duals of the coupling constraints. In addition, we prove that the pricing game admits a unique variational equilibrium. We propose two online learning algorithms to compute solutions to the market mechanisms. A third fully distributed algorithm based on a proximal method is proposed to compute the variational equilibrium solution to the pricing game. Finally, we run numerical simulations to analyse the economic properties of the market mechanisms and the convergence rates of the algorithms.Lire moins >
Lire la suite >We consider a marketplace in the context of 5G network slicing, where service providers (SP), i.e., slice tenants, are in competition for the access to the network resource owned by an infrastructure provider who relies on network slicing. We model the interactions between the end-users (followers) and the SPs (leaders) as a Stackelberg game. We prove that the competition between the SPs results in a multi-resource Tullock rent-seeking game. To determine resource pricing and allocation, we devise two innovative market mechanisms. First, we assume that the SPs are pre-assigned with fixed shares (budgets) of infrastructure, and rely on a trading post mechanism to allocate the resource. Under this mechanism, the SPs can redistribute their budgets in bids and customise their allocations to maximise their profits. We prove that their decision problems give rise to a noncooperative game, which admits a unique Nash equilibrium when dealing with a single resource. Second, when SPs have no bound on their budget, we formulate the problem as a pricing game with coupling constraints and derive the market prices as the duals of the coupling constraints. In addition, we prove that the pricing game admits a unique variational equilibrium. We propose two online learning algorithms to compute solutions to the market mechanisms. A third fully distributed algorithm based on a proximal method is proposed to compute the variational equilibrium solution to the pricing game. Finally, we run numerical simulations to analyse the economic properties of the market mechanisms and the convergence rates of the algorithms.Lire moins >
Langue :
Anglais
Collections :
Source :
Fichiers
- https://hal.inria.fr/hal-03519362v2/document
- Accès libre
- Accéder au document
- document
- Accès libre
- Accéder au document
- FINAL%20VERSION.pdf
- Accès libre
- Accéder au document