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 used
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