Overview

The research project VINO deals with mathematical models and solution methods for problems that arise from the dynamic of modern ICT-networks. Regarding the requirements of the operators and users of such networks particular focus lies on the dynamic optimization of Flexgrid optical transport networks as well as on the embedding of virtual networks into physical substrate networks. The goal of the project is the development of new mathematical approaches, which provide solutions of both problem classes under consideration of temporal changes of the data and requests. Furthermore, the aim is the development and implementation of algorithms, which build the basis for practically applicable tools.

The project is divided into four subprojects, each focusing on a particular aspect of the whole project. These are 1) multi-period-optimization under consideration of temporal, non-stochastic changes, 2) static, detailed models for the generation of bounds for comparison purposes, 3) pro-active long-term planning models under uncertainties and 4) online-optimization and fast reconfiguration algorithms. An important aspect throughout the project is the active exchange between the subprojects and the corporation with our industrial partners.

The results of the research project will be made available to the involved companies. This includes the developed algorithms and software prototypes as well as relevant know-how gained in the project, giving the partners an advantage in the competition.

Subprojects

Project 1: Modellaggregation für zeitdiskrete und ereignisbasierte Modelle

(Model aggregation for time discretized and event based models)

Uni Kassel

Applied Discrete Mathematics
University of Kassel,
Prof. Dr. Andreas Bley

This subproject aims at the development of efficient mathematical approaches for dynamic temporal aspects in mid-term and long-term optimization of networks. Main aspects are reduction and adaption techniques for time discretized and event based linear mixed-integer optimization models, which include both, approaches for a-priori aggregation as well as adaptive aggregation during the solution process. This allows to improve the practical tractability and the temporal resolution of these models so that practically relevant solutions can be obtain in reasonable time.

Project 2: Proaktive Optimierungsmodelle für Netze mit unsicheren Anforderungen

(Proactive optimization model for networks with reliability requirements)

RWTH Aachen

Lehrstuhl II für Mathematik
RWTH Aachen University

Prof. Dr. Arie M.C.A. Koster
    Dr. Stefano Coniglio,
    M.Sc. Martin Tieves

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. Read more ..

Project 3: Detaillierte und skalierbare mathematische Modelle für das VNE-Problem

Zuse-Institut Berlin

(Detailed and scalable mathematical models for the VNE problem)

Optimization Group
Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB)
Dr. Axel Werner

The aim of this subproject is to provide solutions for network embedding problems that obey as many detailed and technical side constraints as possible. This can be seen as a "snapshot" version of the dynamic VNE problems investigated by the partner projects. A comparison with such "ideal" solutions allows to estimate the quality of the solutions produced under the various prerequisites considered in the partner projects and a thorough analysis gives hints as to which aspects of the problem are particularly tricky to incorporate.

Project 4: Online-Algorithmen und Rekonfiguration im laufenden Netzbetrieb

Communication Networks
Chemnitz University of Technology
Prof. Dr.-Ing. Thomas Bauschert

Industrial partners

ADVA Optical Networking SE
Contact: Dr. Achim Autenrieth

Deutsche Telekom AG
Innovation Laboratories
Contact: Dr. Stefan Schmid, Dr. Fritz-Joachim Westphal

Nokia Siemens Networks Management International GmbH
Contact: Ernst-Dieter Schmidt

Meetings

Title Location Date
Kick-Off Kassel 16.12 - 17.12.2013
Modelling-Meeting Berlin, T-Labs 05.02.2014
Project Meeting Technische Universität Chemnitz 15.12.2014 - 16.12.2014
Project Meeting RWTH Aachen University 01.06.2015 - 02.06.2015
Project Meeting Zuse Institute Berlin 30.11.2015 - 01.12.2015
Project Meeting University of Kassel 16.06.2016 - 17.06.2016

Publications

8 results
2015
[8] Optimal offline virtual network embedding with rent-at-bulk aspects (, , , , ), In CoRR, volume abs/1501.07887, .
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[7]On the generation of cutting planes which maximize the bound improvement (, ), In International Symposium on Experimental Algorithms (SEA), .
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[6] Network design with compression: complexity and algorithms (, ), In INFORMS Computing Society Conference (INFORMS ICS), .
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[5]On the computational complexity of the virtual network embedding problem (, , , ), In International Network Optimization Conference (INOC), .
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[4]Virtual network embedding under uncertainty: exact and heuristic approaches (, , ), In Design of Reliable Communication Networks (DRCN), .
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[3]Online Routing and Spectrum Assignment in Flexgrid Optical Networks (, ), In International Conference on Transparent Optical Networks, .
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[2] Mobile core network virtualization: A model for combined virtual core network function placement and topology optimization (, , ), In Proceedings of the 1st IEEE Conference on Network Softwarization, NetSoft 2015, London, United Kingdom, April 13-17, 2015, .
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2014
[1] Maximum throughput network routing subject to fair flow allocation (, , ), In Combinatorial Optimization, LNCS, volume 8596, .
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Presentations

25 results
2015
[25]Bound optimal cutting planes: on the genration of cuts which maximize the bound improvement (, ), . (Annual Conference of the French Operations Research Society (ROADEF))
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[24]On the generation of cutting planes which maximize the bound improvement (, ), . (International Symposium on Experimental Algorithms (SEA))
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[23]Robust optimization approaches for virtual network service providers (, , ), . (International Network Optimization Converence (INOC))
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[22]Network design with compression: the difficulty of compressor placement (, ), . (International Network Optimization Converence (INOC))
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[21]On the computational complexity of the virtual network embedding problem (, , , ), . (International Network Optimization Converence (INOC))
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[20]Virtual Network Embedding under Uncertainty: Exact and Heuristic Approaches (, , ), . (Design of Reliable Communication Networks (DRCN))
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[19]Network Design with Compression: Complexity and Algorithms (, ), . (INFORMS Computing Society Conference(ICS))
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2014
[18]Complexity results for network design with compression (, ), . (International Conference on Operations Research (GOR))
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[17]Network design under multisource uncertainty (, ), . (Conference of the International Federation of Operational Research Societies (IFORS))
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[16]On the Complexity of Network Design with Compression (, ), . (SophiaTech networks seminar)
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[15]Network Design under Compression and Caching Rates Uncertainty (, ), . (SIAM Conference on Optimization)
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[14]On the exact separation of rank inequalities for the maximum stable set problem (, ), . (Integer Programming and Combinatorial Optimizaton (IPCO), Poster)
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[13]Complexity of Network Design with Caching (, ), . (Treewidth And Combinatorial Optimization (TACO) Day)
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[12]On the exact separation of rank inequalities for the stable set problem" (, ), . (International Symposium on Combinatorial Optimization (ISCO))
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[11]A modeling framework for multiple sources of data uncertainty in combinatorial optimization problems (, ), . (International Symposium on Combinatorial Optimization (ISCO))
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[10]Bilevel optimization models for traffic engineering with elastic demands and fair flow allocation (, , , ), . (INFORMS Telecommunications Conference (INFORMS TELECOM))
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[9]Network design with compression II: a complexity study (, ), . (INFORMS Telecommunications Conference (INFORMS TELECOM))
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[8]Virtual Network Embedding: Models, Complexity, and Computations (), . (Seminar Université Libre de Bruxelles)
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[7]Novel Approaches to Network Design (), . (Jahrestagung der Österreichischen Gesellschaft für Operations Research (ÖGOR))
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[6]On the exact separation of rank inequalities for the maximum stable set problem (, ), . (Invited Seminar, Zuse Institute Berlin(ZIB))
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[5]Robust optimization approaches to virtual network embedding (, , ), . (INFORMS Annual Meeting (INFORMS))
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[4]Virtual network embedding with network design elements: reservation of physical resources (, , ), . (INFORMS Annual Meeting (INFORMS))
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[3]On the generation of cuts which maximize the bound improvement (, ), . (Annual Conference of the Italian Operational Research Society (AIRO))
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[2]Network design with compression I: a polyhedral study (, ), . (INFORMS Telecommunications Conference (INFORMS TELECOM))
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[1]Models for Virtual Network Embedding Problems with Time Restrictions (, ), . (International Conference On Operations Research 2014)
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