Robustness in Communication Networks: Scenarios and Mathematical Approaches

The planning of wide-area networks to achieve robust operation is an ongoing challenge for network providers. Robust means to ensure stable operation of a network in case of fault occurrence. In this paper several scenarios in the context of the German Research Network are discussed to point out robustness aspects in a more detailed manner. The approach to address these challenges is to apply mathematical methods, more precisely exact and approximate integer linear programming and fast combinatorial algorithms.

[1]  Sebastian Orlowski,et al.  Optimal Design of Survivable Multi-layer Telecommunication Networks , 2009 .

[2]  Mikkel Thorup,et al.  Increasing Internet Capacity Using Local Search , 2004, Comput. Optim. Appl..

[3]  Celso C. Ribeiro,et al.  Design of Survivable Networks: A survey , 2005 .

[4]  Arnaud Knippel,et al.  The multi-layered network design problem , 2007, Eur. J. Oper. Res..

[5]  Andreas Bley,et al.  Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin a Lagrangian Approach for Integrated Network Design and Routing in Ip Networks a Lagrangian Approach for Integrated Network Design and Routing in Ip Networks * , 2022 .

[6]  Celso C. Ribeiro,et al.  A hybrid genetic algorithm for the weight setting problem in OSPF/IS‐IS routing , 2005, Networks.

[7]  Michael Menth,et al.  Greedy design of resilient multi-layer networks , 2010, 6th EURO-NGI Conference on Next Generation Internet.

[8]  Andreas Bley An Integer Programming Algorithm for Routing Optimization in IP Networks , 2009, Algorithmica.

[9]  John N. Tsitsiklis,et al.  Introduction to linear optimization , 1997, Athena scientific optimization and computation series.

[10]  Michal Pioro,et al.  Optimization of administrative weights in IP networks using branch-and-cut approach , 2005 .

[11]  Bernard Fortz,et al.  Fast heuristic techniques for intra-domain routing metric optimization , 2007 .

[12]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[13]  Professor Dr. Klaus Neumann,et al.  Project Scheduling with Time Windows and Scarce Resources , 2003, Springer Berlin Heidelberg.