Suche nach „[C.] [Linnhoff-Popien]“ hat 2 Publikationen gefunden
Suchergebnis als PDF
    DigitalF: Elektrotechnik und Medientechnik


    M. Beck, Andreas Fischer, J. Botero, C. Linnhoff-Popien, H. Meer

    Distributed and scalable embedding of virtual networks

    Journal of Network and Computer Applications, vol. 56, no. October, pp. 124-136


    DOI: 10.1016/j.jnca.2015.06.012

    Abstract anzeigen

    Abstract Network virtualization is widely regarded as a key technology for the Future Internet, enabling the deployment of new network protocols without changing dissimilar hardware devices. This leads to the problem of mapping virtual demands to physical resources, known as Virtual Network Embedding (VNE). Current VNE algorithms do not scale with respect to the substrate network size. Therefore, these algorithms are not applicable in large-scale scenarios where virtual networks have to be embedded in a timely manner. This paper discusses DPVNE, a Distributed and Generic VNE framework: It runs cost-oriented centralized embedding algorithms in a distributed way, spreading workload across the substrate network instead of concentrating it on one single node (as centralized algorithms do). Several state-of-the-art algorithms were evaluated running inside the DPVNE framework. Results show that DPVNE leads to runtime improvements in large-scale scenarios and embedding results are kept comparable.

    DigitalF: Elektrotechnik und Medientechnik

    Beitrag (Sammelband oder Tagungsband)

    M. Beck, Andreas Fischer, F. Kokot, C. Linnhoff-Popien, H. Meer

    A Simulation Framework for Virtual Network Embedding Algorithms

    Proceedings of the 16th International Telecommunications Network Strategy and Planning Symposium (Networks 2014) [Funchal, Madeira Island, Portugal; September 17-19, 2014]


    DOI: 10.1109/NETWKS.2014.6959238

    Abstract anzeigen

    Network virtualization is seen as an enabling technology for the Future Internet. In this context, many Virtual Network Embedding algorithms have been introduced in literature so far. This paper discusses an open source framework for the evaluation of such algorithms. The paper describes features provided by the framework, how to use the framework for evaluating these algorithms, and how to extend the software with respect to novel algorithms and simulation scenarios. Lessons learned are presented, describing how the software evolved towards a mature and highly extensible simulation framework.