Suche nach „[M.] [Duelli]“ hat 4 Publikationen gefunden

DigitalElektrotechnik und Medientechnik

Zeitschriftenartikel

J. Botero, X. Hesselbach, M. Duelli, D. Schlosser, Andreas Fischer, H. Meer

Energy Efficient Virtual Network Embedding

IEEE Communications Letters, vol. 16, no. 5, pp. 756-759

2012

DOI: 10.1109/LCOMM.2012.030912.120082

Abstract anzeigen

Waste of energy due to over-provisioning and overdimensioning of network infrastructures has recently stimulated the interest on energy consumption reduction by Internet Service Providers (ISPs). By means of resource consolidation, network virtualization based architectures will enable energy saving. In this letter, we extend the well-known virtual network embedding problem (VNE) to energy awareness and propose a mixed integer program (MIP) which provides optimal energy efficient embeddings. Simulation results show the energy gains of the proposed MIP over the existing cost-based VNE approach.

DigitalElektrotechnik und Medientechnik

Beitrag (Sammelband oder Tagungsband)

M. Duelli, D. Schlosser, J. Botero, X. Hesselbach, Andreas Fischer, H. Meer

VNREAL: Virtual Network Resource Embedding Algorithms in the Framework ALEVIN

Proceedings of the 7th Euro-NF Conference on Next-Generation Internet (NGI 2011) [Kaiserslautern; June 27-29, 2011]

2011

DOI: 10.1109/NGI.2011.5985874

Abstract anzeigen

Network virtualization is recognized as an enabling technology for the Future Internet that overcomes network ossification. However, it introduces a set of challenges. In any network virtualization environment, the problem of optimally mapping virtual resources to physical resources, known as virtual network embedding (VNE), is a critical challenge. Several algorithms attempting to solve this problem have been proposed in literature, so far. However, comparison of existing and new VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, the VNREAL project introduces ALEVIN, a framework to compare different algorithms according to a set of metrics, easily incorporate new VNE algorithms, and evaluate these algorithms on a given scenario for arbitrary parameters.

DigitalElektrotechnik und Medientechnik

Beitrag (Sammelband oder Tagungsband)

J. Botero, X. Hesselbach, M. Duelli, D. Schlosser, Andreas Fischer, H. Meer

Flexible VNE Algorithms Analysis using ALEVIN

Proceedings of the 11th Würzburg Workshop on IP: Joint ITG and Euro-NF Workshop "Visions of Future Generation Networks" (EuroView2011)

2011

Abstract anzeigen

Network virtualization is recognized as an enabling technology for the Future Internet that overcomes network ossification. However, it introduces a set of challenges. In any network virtualization environment, the problem of optimally mapping virtual demands to physical resources, known as virtual network embedding (VNE), is a crucial challenge. This paper analyses the behaviour of the main algorithms proposed to solve VNE by means of the ALEVIN framework. The VNE algorithms are evaluated with regard to appropriate metrics such as: cost, revenue, and virtual network acceptance ratio. We also analyse the impact of the recently introduced hidden hop demand concept in the performance of the VNE algorithms.

DigitalElektrotechnik und Medientechnik

Zeitschriftenartikel

Andreas Fischer, J. Botero, M. Duelli, D. Schlosser, X. Hesselbach, H. Meer, T. Margaria, J. Padberg, G. Taentzer, H. Hellbrück, N. Luttenberger, V. Turau

ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms

Electronic Communications of the EASST, vol. 37, pp. 1-12

2011

Abstract anzeigen

Network virtualization is recognized as an enabling technology for the Future Internet. Applying virtualization of network resources leads to the problem of mapping virtual resources to physical resources, known as “Virtual Network Embedding” (VNE). Several algorithms attempting to solve this problem have been discussed in the literature, so far. However, comparison of VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, we introduce a framework to compare different algorithms according to a set of metrics, which allow to evaluate the algorithms and compute their results on a given scenario for arbitrary parameters.