We develop a new optical switching fabric with multi-granularity grooming based on our lambda-group model, as well as algorithms that can handle dynamic environments. The proposed fabric based on a new multi-granular grooming scheme presents the distinctive approach of assigning different contiguous groups of granularities to different paths for effective treatment. Results and figures from experiments show that the particular partitioning approach not only is helpful to port reduction significantly, but also improves the SNR of signal and blocking performance for dynamic connection requests.

Based on traffic prediction, a new reservation method is proposed to reduce delay and void filling ratio at edge node of optical burst switching networks. Simulation studies show that our method achieves an important improvement and has a dynamic optimum weight value in a certain offset time.