A Predictive and Incremental Grooming Scheme for Time-varying Traffic in WDM Networks

Traffic grooming can effectively utilize the transmission capacity of WDM networks by properly multiplexing low-speed traffic flows onto high-capacity wavelength channels. In order to maximize the wavelength resource and cut down network costs associated with, e.g. OEO conversion for time-varying yet predictable traffic, we propose a novel predictive and incremental (PI) traffic grooming scheme, named PI-grooming. A conventional traffic grooming approach for fluctuated traffic is to run an algorithm that (re)assigns the traffic flows to as a few wavelengths as possible based only on the current traffic demands of these flows. This however will lead to a lot of OEO traffic. The proposed PI-grooming considers the existing flow assignment, the current traffic demands, and the expected traffic demands in the near future. We show that, compared with the conventional approach, PI-grooming can effectively minimize the amount of OEO traffic while still using a very small number of wavelengths.