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Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7832))

Abstract

The Virtual Network Mapping Problem arises in the context of Future Internet research. Multiple virtual networks with different characteristics are defined to suit specific applications. These virtual networks, with all of the resources they require, need to be realized in one physical network in a most cost effective way. Two properties make this problem challenging: Already finding any valid mapping of all virtual networks into the physical network without exceeding the resource capacities is NP-hard, and the problem consists of two strongly dependent stages as the implementation of a virtual network’s connections can only be decided once the locations of the virtual nodes in the physical network are fixed. In this work we introduce various construction heuristics, Local Search and Variable Neighborhood Descent approaches and perform an extensive computational study to evaluate the strengths and weaknesses of each proposed solution method.

This work has been funded by the Vienna Science and Technology Fund (WWTF) through project ICT10-027.

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Authors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria

    Johannes Inführ & Günther R. Raidl

Authors
  1. Johannes Inführ
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  2. Günther R. Raidl
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Leipzig, Johannisgasse 26, 04103, Leipzig, Germany

    Martin Middendorf

  2. IKERBASQUE, Basque Foundation for Science, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, Donostia, Spain

    Christian Blum

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Inführ, J., Raidl, G.R. (2013). Solving the Virtual Network Mapping Problem with Construction Heuristics, Local Search and Variable Neighborhood Descent. In: Middendorf, M., Blum, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2013. Lecture Notes in Computer Science, vol 7832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37198-1_22

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  • DOI: https://doi.org/10.1007/978-3-642-37198-1_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37197-4

  • Online ISBN: 978-3-642-37198-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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