J
Juan Felipe Botero
Researcher at University of Antioquia
Publications - 64
Citations - 3113
Juan Felipe Botero is an academic researcher from University of Antioquia. The author has contributed to research in topics: Virtualization & Network virtualization. The author has an hindex of 17, co-authored 58 publications receiving 2630 citations. Previous affiliations of Juan Felipe Botero include University of Passau & Polytechnic University of Catalonia.
Papers
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Journal ArticleDOI
Virtual Network Embedding: A Survey
TL;DR: A survey of current research in the Virtual Network Embedding (VNE) area is presented and a taxonomy of current approaches to the VNE problem is provided and opportunities for further research are discussed.
Journal ArticleDOI
Resource Allocation in NFV: A Comprehensive Survey
TL;DR: This paper presents a comprehensive state of the art of NFV-RA by introducing a novel classification of the main approaches that pose solutions to solve the NFV resource allocation problem.
Journal ArticleDOI
Energy Efficient Virtual Network Embedding
Juan Felipe Botero,Xavier Hesselbach,Michael Duelli,Daniel Schlosser,Andreas Fischer,H. de Meer +5 more
TL;DR: The well-known virtual network embedding problem (VNE) is extended to energy awareness and a mixed integer program (MIP) which provides optimal energy efficient embeddings is proposed which shows energy gains over the existing cost-based VNE approach.
Proceedings ArticleDOI
Coordinated Allocation of Service Function Chains
TL;DR: CoordVNF is proposed, a heuristic method to coordinate the composition of VNF chains and their embedding into the substrate network that aims to minimize bandwidth utilization while computing results within reasonable runtime.
Journal ArticleDOI
ALEVIN - A framework to develop, compare, and analyze virtual network embedding algorithms
Andreas Fischer,Juan Felipe Botero,Michael Duelli,Daniel Schlosser,Xavier Hesselbach,Hermann de Meer +5 more
TL;DR: This work introduces 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.