The dense wavelength division multiplexing (DWDM) technique has been developed to provide a tremendous number of wavelengths/channels in an optical fiber. In the multi-channel networks, it has been a challenge to effectively schedule a given number of wavelengths and variable-length packets into different wavelengths in order to achieve a maximal network throughput. This optimization process has been considered as difficult as the job scheduling in multiprocessor scenario, which is well known as a NP-hard problem. In current research, a heuristic method, genetic algorithms (GAs), is often employed to obtain the near-optimal solution because of its convergent property. Unfortunately, the convergent speed of conventional GAs cannot meet the speed requirement in high-speed networks. In this paper, we propose a novel hyper-generation GAs (HG-GA) concept to approach the fast convergence. By the HG-GA, a pipelined mechanism can be adopted to speed up the chromosome generating process. Due to the fast convergent property of HG-GA which becomes possible to provide an efficient scheduler for switching variable-length packets in high-speed and multi-channel optical networks. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Sheu, S. T., Chuang, Y. R., Chen, Y. H., & Lai, E. (2003). An optimization solution for packet scheduling: A pipeline-based genetic algorithm accelerator. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2723, 681–692. https://doi.org/10.1007/3-540-45105-6_83
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