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Computing optimal routes in massively dense ad-hoc networks becomes intractable as the number of nodes becomes very large. One recent approach to solve this problem is to use a fluid type approximation in which the whole network is replaced by a continuum plain. Various paradigms from physics have been used recently in order to solve the continuum model. We consider massively dense ad-hoc networks and study their continuum limits as the node density increases and as the graph providing the available routes becomes a continuous area with location and congestion dependent costs. We study both the global optimal solution as well as the non-cooperative routing problem among a large population of users where each user seeks a path from its source to its destination so as to minimize its individual cost. We seek for a (continuum version of the) Wardrop equilibrium. We first show how to derive meaningful cost models as a function of the scaling properties of the capacity of the network as a function of the density of nodes. We present various solution methodologies for the problem: (1) the viscosity solution of the Hamilton-Bellman-Jacobi equation, for the global optimization problem, (2) a method based on Green Theorem for the least cost problem of an individual, and (3) a solution of the Wardrop equilibrium problem using a transformation into an equivalent global optimization problem. SHORT BIOGRAPHY: Alonso Silva was born in Santiago, Chile. He received his B.Sc of Engineering and his Mathematical Engineering degree from the Universidad de Chile, in 2004 and 2006 respectively. Currently, he is pursuing his Ph.D. degree at Maestro Team at INRIA and Chaire Alcatel-Lucent at Supelec. His thesis advisor is prof. Eitan Altman and his thesis co- advisor is prof. Merouane Debbah. His research interests include optimal transportation, game theory. markov decision processes, and random matrix theory.
Merouane Debbah