Communication Dans Un Congrès Année : 2024

Client-Constrained Virtual Network Embedding under Uncertainty

Résumé

This paper addresses uncertainty in resource demands and heterogeneous requests with affinity and anti-affinity constraints on virtual nodes and links in traditional Virtual Network Embedding. This is realized using stochastic modeling and methods based on an initial Integer-Linear Programming (ILP) model formulation of the VNE problem. The ILP is extended to build a non-linear Chance-Constrained Programming (CCP) model to address uncertainty. The derived CCP model is then linearized for exploitation by standard solvers. Numerical experiments and comparisons with state-of-the-art methods illustrate the efficiency of our approaches. The results provide insight to cloud service providers on their resource investment to serve clients with affinity and anti-affinity requirements under uncertainty.
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Dates et versions

hal-04881171 , version 1 (11-01-2025)

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Citer

Junkai He, Makhlouf Hadji, Djamal Zeghlache. Client-Constrained Virtual Network Embedding under Uncertainty. 49th IEEE Conference on Local Computer Networks (LCN), Oct 2024, Caen, France. pp.1-7, ⟨10.1109/LCN60385.2024.10639733⟩. ⟨hal-04881171⟩
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