Project 2: Proaktive Optimierungsmodelle für Netze mit unsicheren Anforderungen
(Proactive optimization model for networks with reliability requirements)
Affiliation
Lehrstuhl II für Mathematik
RWTH Aachen University
Prof. Dr. Arie M.C.A. Koster
Dr. Stefano Coniglio,
M.Sc. Martin Tieves
Content
The subproject aims at providing solutions to the VNE and Flexgrid problems in cases of data uncertainty. We assume that the nominal data taken as input for the two problems might differ from the real data due to, e.g., measurement errors or unpredictable changes in what was considered as a given. In this setting, the focus is on defining so-called uncertainty sets, representing (explicitly or implicitly) a set of realistic scenarios, e.g., of realizations of the uncertain data. Mathematical models and optimization algorithms are then designed so to produce solutions that are robust under uncertainty, i.e., feasible with respect to all the realizations described in the uncertainty sets.
Poster
In the context of the DRCN conference 2015, we prepared a poster summarizing the results of our paper on robust virtual network embedding. Click on the picture to download.
Publications
2015 | |
[6] | Optimal offline virtual network embedding with rent-at-bulk aspects ( ), In CoRR, volume abs/1501.07887, 2015. |
[5] | On the generation of cutting planes which maximize the bound improvement ( ), In International Symposium on Experimental Algorithms (SEA), 2015. |
[4] | Network design with compression: complexity and algorithms ( ), In INFORMS Computing Society Conference (INFORMS ICS), 2015. |
[3] | On the computational complexity of the virtual network embedding problem ( ), In International Network Optimization Conference (INOC), 2015. |
[2] | Virtual network embedding under uncertainty: exact and heuristic approaches ( ), In Design of Reliable Communication Networks (DRCN), 2015. |
2014 | |
[1] | Maximum throughput network routing subject to fair flow allocation ( ), In Combinatorial Optimization, LNCS, volume 8596, 2014. |