With the rapid development of cloud computing, big data technology, and Data Center(DC), the scale and number of DC continue to expand, and the bandwidth resources and energy consumption of optical networks is also growing rapidly. It can be seen that the method can effectively reduce both bandwidth resources and energy consumption in the network has received widespread attention.

Considering the characteristics of both the network energy consuming components, the spectrum resource allocation, and the selection of different modulation formats, we employ both adaptive traffic grooming method and a spectrum layering method for network traffic grooming. A Distance-adaptive Stratification Grooming Method (DSGM) in elastic optical networks is also proposed. We can employ the adaptive selection of different modulation formats to divide spectrum resources into different spectrum layers for network traffic grooming. In this way, on the one hand, the distance adaptive modulation method can select different modulation formats based on the length of the connection request working path. On the other hand, based on the spectrum layered traffic grooming method, the idle spectrum resources of each fiber link are layered according to different rates of optical channels. The appropriate optical channels are selected for traffic grooming through optimizing the use of spectrum resources based on the remaining bandwidth resources of the fiber links. We also introduce three different traffic grooming methods for comparison, including Spectrum Stratification Grooming Method (SSGM), Traditional Traffic Grooming Method (TTGM), and Traditional Method Without Grooming (TMWG).

The simulation results show that the proposed approach significantly reduces the energy consumption, and the blocking probability. It also improves the network spectrum efficiency compared with SSGM, TTGM, and TMWG method.

We can realize the network resource optimization by using the stratification traffic grooming methods in elastic optical networks.