Clasificación de parámetros y criterios al ensamblar la ráfaga

This article presents a classification of some of the algorithms or mechanisms for assembling burst of data existing in the scientific literature of the networks switching optical of burst, based on the different parameters and criteria that affect of assembly process. Marking out, that this classification is the result of the revision stage of the "state of the art" in the degree work entitled "Adaptive Algorithm based on fuzzy logic and PSO for the assembly of bursts in a distributed network of OBS", at level master's degree. The way in which the burst is assembled is of great importance, since it is the process manage´s the loading of incoming traffic to a network and in this way manages the performance of the entire network. In some cases, the performance is analyzed in terms of the probability of blockage and in the end-to-end delay of the transmitted bursts, among other parameters. The results will help new researchers, interested in the optical networks and more in the process of assembly, have a synthesis of the basic concepts of optical switching networks, know and differentiate the parameters and criteria that affect when assembling a burst of data, pointing out some of the combinations that have been applied in other works. Also, be able to identify some of the potential problems open on this topic.Este artículo presenta una clasificación de algunos de los algoritmos o mecanismos para ensamblar la ráfaga de datos existentes en la literatura científica de las redes de conmutación óptica de ráfagas, basándose en los diferentes parámetros y criterios que inciden en el proceso de ensamblaje. Resaltando, que dicha clasificación es el resultado de la etapa de revisión del estado del arte en el trabajo de grado titulado “Algoritmo Adaptativo basado en la Lógica Difusa y PSO para el Ensamble de Ráfagas en una red OBS Distribuida”, a nivel de maestría. La forma en que se ensambla la ráfaga es de gran importancia ya que es el proceso que gestiona la carga de tráfico entrante a una red y de esta manera gestiona el desempeño de toda la red. En algunos casos, el desempeño es analizado en cuanto a la probabilidad de bloqueo y en el retardo de extremo a extremo de las ráfagas transmitidas, entre otros parámetros. Los resultados ayudaran a los nuevos investigadores, interesados en las redes ópticas y más en el proceso de ensamblaje, tener una introducción general de las redes de conmutación óptica, conocer y diferenciar los parámetros y criterios que inciden a la hora de ensamblar una ráfaga de datos, señalando algunas de las combinaciones que se han aplicado en otros trabajos. Además, poder identificar algunos de los problemas potenciales abiertos en este tema

Burst Loss Reduction Using Fuzzy-Based Adaptive Burst Length Assembly Technique for Optical Burst Switched Networks

The optical burst switching (OBS) paradigm is perceived as an intermediate switching technology prior to the realization of an all-optical network. Burst assembly is the first process that takes place at the edge of an OBS network.  It is crucial to the performance of an OBS network because it greatly influences loss and delay on such networks.  Burst assembly is an important process while  burst loss ratio (BLR) and delay are important issues in OBS.  In this paper, an intelligent burst assembly algorithm called a Fuzzy-based Adaptive Length Burst Assembly (FALBA) algorithm that is based on fuzzy logic and tuning of fuzzy logic parameters is proposed for OBS network. FALBA was evaluated against itself and the fuzzy adaptive threshold (FAT) burst assembly algorithm using 12 configurations via simulation. The 12 configurations were derived from three rule sets (denoted 0,1,2), two defuzzification techniques (Centroid [C]and Largest of Maximum[L]) and two aggregation methods (Max[M] and Sum[S]) of fuzzy logic.  Simulation results have shown that FALBA0LM has the best BLR performance when compared to its other configurations and the FAT. However, with respect to delay, FAT only outperforms all configurations of FALBA at low loads (0.0-0.4) but the performance of FAT also decreases as the load (0.4-1.0) increases. Therefore, at high loads (0.4-1.0)  FALBA2CS has the best delay performance. Our results deduce that FALBA0LM can be use