A novel performance metric for Virtual Network Embedding combining aspects of Blocking Probability and Embedding Cost

Network Virtualization offers a solution for Future Internet and it is a key enabler for cloud computing applications. Virtual Network Embedding (VNE) problem deals with resource allocation of a physical infrastructure to Virtual Network Requests (VNRs). Several performance metrics are employed in order to evaluate the efficiency of specific VNE approaches. These existing metrics, mostly related to Infrastructure Provider profit, are computed at the end of the VNE process, after embedding many VNRs. This work proposes a novel performance metric, VNE-NP (VNE Normalized Profit) which combines aspects of the two metrics most used in the literature: Blocking Probability and Embedding Cost.XII Workshop de Arquitecturas, Redes y Sistemas Opearativos (WARSO).Red de Universidades con Carreras en Informática (RedUNCI

A Multi-Objective Approach for VNE Problems using multiple ILP formulations

Network Virtualization is a key technology for the Future Internet, allowing the deployment of multiple independent virtual networks that use resources of the same basic infrastructure. An important challenge in the dynamic provision of virtual networks resides in the optimal allocation of physical resources (nodes and links) to requirements of virtual networks. This problem is known as Virtual Network Embedding (VNE). For the resolution of this problem, previous research has focused on designing algorithms based on the optimization of a single objective. On the contrary, in this work we present a multi-objective algorithm, called VNE-MO-ILP, for solving dynamic VNE problem, which calculates an approximation of the Pareto Front considering simultaneously resource utilization and load balancing. Experimental results show evidences that the proposed algorithm is better or at least comparable to a state-of-the-art algorithm. Two performance metrics were simultaneously evaluated: (i) Virtual Network Request Acceptance Ratio and (ii) Revenue/Cost Relation. The size of test networks used in the experiments shows that the proposed algorithm scales well in execution times, for networks of 84 nodes

XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI