A bilevel optimization model for load balancing in mobile networks through price incentives

Abstract : We propose a model of incentives for data pricing in large mobile networks, in which an operator wishes to balance the number of connexions (active users) of different classes of users in the different cells and at different time instants, in order to ensure them a sufficient quality of service. We assume that each user has a given total demand per day for different types of applications, which he may assign to different time slots and locations, depending on his own mobility, on his preferences and on price discounts proposed by the operator. We show that this can be cast as a bilevel programming problem with a special structure allowing us to develop a polynomial time decomposition algorithm suitable for large networks. First, we determine the optimal number of connexions (which maximizes a measure of balance); next, we solve an inverse problem and determine the prices generating this traffic. Our results exploit a recently developed application of tropical geometry methods to mixed auction problems, as well as algorithms in discrete convexity (minimization of discrete convex functions in the sense of Murota). We finally present an application on real data provided by Orange and we show the efficiency of the model to reduce the peaks of congestion.
Type de document :
Communication dans un congrès
WiOpt 2017 - 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, May 2017, Paris, France. IEEE, pp.1-8, 〈10.23919/WIOPT.2017.7959902〉
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https://hal.inria.fr/hal-01649042
Contributeur : Marion Pellerin <>
Soumis le : lundi 27 novembre 2017 - 10:40:09
Dernière modification le : jeudi 10 mai 2018 - 02:04:19

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Jean Bernard Eytard, Marianne Akian, Mustapha Bouhtou, Stephane Gaubert. A bilevel optimization model for load balancing in mobile networks through price incentives. WiOpt 2017 - 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, May 2017, Paris, France. IEEE, pp.1-8, 〈10.23919/WIOPT.2017.7959902〉. 〈hal-01649042〉

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