Optimizing the investments in mobile networks and subscriber migrations for a telecommunication operator

We consider the context of a telecommunications company that is at the same time an infrastructure operator and a service provider. When planning its network expansion, the company can leverage over its knowledge of subscribers dynamic to better optimize the network dimensioning, therefore avoiding unnecessary costs. In this work, the network expansion represents the deployment and/or reinforcement of several technologies (e.g. 2G,3G,4G), assuming that subscribers to a given technology can be served by this technology or older ones. The operator can influence subscribers dynamic by subsidies. The planning is made over a discretized time horizon while some strategic guidelines requirements are demanded at the end of the time horizon. Following classical models, we consider that the behavior of customers follows an S-shape piecewise constant function. We propose a Mixed-Integer Linear Programming formulation and a heuristic algorithm for the multi-year planning problem. The scalability of the formulation and the quality of the heuristic are assessed numerically on real instances for a use-case with two generations

A bundle-type algorithm for routing in telecommunication data networks

To optimize the quality of service through a telecommunication network, we propose an algorithm based on Lagrangian relaxation. The bundle-type dual algorithm is adapted to the present situation, where the dual function is the sum of a polyhedral function (coming from shortest paths problems) and of a smooth function (coming from the congestion)

Proceedings of the 6th International Workshop on Design and Reliable Communication Networks (DRCN '07)

International audienc

A minimum mean cycle cancelling method for nonlinear multicommodity flow problems

International audienceWe propose a new method based on minimum mean cycle cancelling for multicommodity flow problems with separable convex cost ruling out saturated capacities. This method is inspired by the cycle cancelling method first worked out by Goldberg and Tarjan for minimum cost circulations (A.V. Goldberg, R.E. Tarjan, Finding minimum-cost circulation by cancelling negative cycles, JACM 36 (4), 1989, pp. 873–886). Convergence of the method is formally proved and a variant with a more flexible selection of cycles is proposed. Also, we report some computational experience on the message routing problem in telecommunication networks using actual and randomly generated networks

Mathematical models of the delay constrained routing problem

Given a network with known link capacities and traffic demands, one can compute the paths to be used and the amount of traffic to be send through each path by solving a classical multi-flow problem. However, more quality of service constraints such as delay constraints, may be imposed and the routing problem becomes difficult to solve. We assume that the delay on each link depends on both its capacity and the total flow on it. We show that satisfying the delay constraints and the capacity constraints is an NP-complete problem. We give a convex relaxation of the delay constrained routing problem and present some ways to get upper and lower bounds on the problem