Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-13T05:56:53.819Z Has data issue: false hasContentIssue false

An approach to robust network designin telecommunications

Published online by Cambridge University Press:  11 October 2007

Georgios Petrou
Affiliation:
France Télécom Division R&D, MCN-OTT, 38-40 rue du Général Leclerc, 92794 Issy-Les-Moulineaux Cedex 9, France; georgios.petrou@orange-ftgroup.com, adam.ouorou@orange-ftgroup.com
Claude Lemaréchal
Affiliation:
Inria, 655 avenue de l'Europe, Montbonnot, 38334 Saint Ismier, France; Claude.Lemarechal@inrialpes.fr
Adam Ouorou
Affiliation:
France Télécom Division R&D, MCN-OTT, 38-40 rue du Général Leclerc, 92794 Issy-Les-Moulineaux Cedex 9, France; georgios.petrou@orange-ftgroup.com, adam.ouorou@orange-ftgroup.com
Get access

Abstract

In telecommunications network design, one of the most frequentproblems is to adjust the capacity on the links of the network in order to satisfy a set of requirements. In the past, theserequirements were demands based on historical data and/or demographic predictions. Nowadays, because of new technologydevelopment and customer movement due to competitiveness, thedemands present considerable variability. Thus, network robustness w.r.t demand uncertainty is now regarded as a majorconsideration. In this work, we propose a min-max-min formulation and a methodology to cope with this uncertainty. We model the uncertainty as the convex hull of certain scenarios and show thatcutting plane methods can be applied to solve the underlying problems. We will compare Kelley, Elzinga-Moore and bundle methods.

Type
Research Article
Copyright
© EDP Sciences, ROADEF, SMAI, 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ben-Ameur, W. and Kerivin, H., Routing of uncertain traffic demands. Optim. Eng. 3 (2005) 283313. CrossRef
A. Ben-Tal and A. Nemirovski, Robust convex optimization. Math. Oper. Res. 23 (1998).
Bonatti, M., Gaivoronski, A., Lemonche, A. and Polese, P., Summary of some traffic engineering studies carried out within RACE project R1044. European Transactions on Telecommunications 5 (1994) 7990.
O. Briant, C. Lemaréchal, Ph. Meurdesoif, S. Michel, N. Perrot and F. Vanderbeck, Technical Report 5453, Inria, 2005. Accepted for publication at Math. Program.
Demyanov, A.V., Demyanov, V.F. and Malozemov, V.N., Minimaxmin problems revisited. Optim. Methods Softw. 17 (2002) 783804. CrossRef
Duffield, N.G., Goyal, P., Greenberg, A., Mishra, P., Ramakrishnan, K.K. and van der Merwe, J.E., Resource managment with hoses: Point-to-cloud services for virtual private networks. IEEE/ACM Trans. Networking 10 (2002) 679692. CrossRef
Elzinga, J. and Moore, T.J., A central cutting plane algorithm for the convex programming problem. Math. Program. 8 (1975) 134145. CrossRef
Frangioni, A., Solving semidefinite quadratic problems within nonsmooth optimization algorithms. Comput. Oper. Res. 23 (1996) 10991118. CrossRef
Goffin, J.-L., Haurie, A. and Vial, J.-Ph., Decomposition and nondifferentiable optimization with the projective algorithm. Manage. Sci. 38 (1992) 284302. CrossRef
Higle, J.L. and Sen, S., Stochastic decomposition: An algorithm for two-stage linear programs with recourse. Math. Oper. Res. 16 (1991) 650669. CrossRef
J.-B. Hiriart-Urruty and C. Lemaréchal, Convex Analysis and Minimization Algorithms. Springer-Verlag, Berlin (1993).
G.F. Italiano, S. Leonardi and G. Oriolo, Design of networks in the hose model, in 2nd International Workshop on Approximation and Randomization Algorithms in Communication Networks, Carleton Scientific Press (2002) 65–76.
Kelley, J.E., The cutting plane method for solving convex programs. J. Appl. Math. SIAM 8 (1960) 703712. CrossRef
Kiwiel, K., Proximity control in bundle methods for convex nondifferentiable minimization. Math. Program. 46 (1990) 105122. CrossRef
Kiwiel, K., A cholesky dual method for proximal piecewise linear programming. Numer. Math. 68 (1994) 325340. CrossRef
P. Kouvelis and G. Yu, Robust Discrete Optimization and Its Applications. Kluwer Academic Publishers (1997).
Kumar, A., Rastogi, R., Silberschatz, A. and Yener, B., Algorithms for provisioning virtual private networks in the hose model. IEEE/ACM Trans. Networking 10 (2002) 565578. CrossRef
C. Lemaréchal, Lagrangian relaxation, in Computational Combinatorial Optimization, Optimal or Provably Near-Optimal Solutions [based on a Spring School] 2241, London, UK . Springer-Verlag (2001) 112–156.
A. Lisser, A. Ouorou, J.-Ph. Vial and J. Gondzio, Capacity planning under uncertain demand in telecommunication networks. Technical Report 99.13, Logilab, Department of Management Studies, University of Geneva, Switzerland, October 1999.
Lucertini, M. and Paletta, G., A class of network design problems with multiple demand: Model formulation and an algorithmic approach. Math. Program. Stud. 26 (1986) 225228. CrossRef
Nemhauser, G.L. and Widhelm, W.B., A modified linear program for columnar methods in mathematical programming. Oper. Res. 19 (1971) 10511060. CrossRef
Ouorou, A., Robust capacity assignment in telecommunications. Comput. Manage. Sci. 3 (2006) 285305. CrossRef
Sen, S., Doverspike, R.D. and Cosares, S., Network planning with random demand. Telecommun. Syst. 3 (1994) 1130. CrossRef