MULTI-LAYER GROOMING DESIGN FOR NETWORK PLANNING TOOL IN 400G ERA

The introduction of digital coherent optics has permitted carriers to maintain a profit and a flat capital expenditure despite the constant traffic increase and the stagnant pool of subscribers over the last years. Nowadays, all these coherent devices are capable of transmitting at 400 Gb/s. The two categories available are the standard interfaces (400ZR/OpenZR+) and the proprietary interfaces (Multi-haul). These 400 Gb/s devices are classified by considering their properties and scope, and allow full coverage in the network. Moreover, due to their size, power consumption, and heat dissipation, such devices may be integrated within IP routers enabling a technological convergence toward IP-optical (IPoDWDM) networking. IPoDWDM results to be one of the best technologies for reducing the space and carbon footprint of the telecommunication business and provides many realization possibilities. Nevertheless, because the Shannon's limit is almost reached, it will no longer be possible to increase the capacity of coherent devices in order to accommodate the relentless demand, therefore it is necessary to understand how to optimize the management and exploitation of resources in the network. One way to achieve that objective is to use network planning tools providing optimized network designs. This work proposes a model to perform multi-layer grooming design in a heuristic network planning tool able to handle design solutions for multi-layer networks. The design of multi-layer scenarios for both long-term and real-time planning is obtained by implementing novel grooming policies, which are useful to attain the requirements on time computation performance. We also suggest a traffic-request selection sort for increasing the probability of traffic aggregation and a software optimization to speed up the algorithm when end-to-end multiplexing is possible. Therefore, thanks to the modeling and the implementation of routing constraints, the model adapts to the planning of different network architectures (e.g., opaque, transparent, translucent) that could be compared later. The comparison has been used to point out the strengths and weaknesses of each architecture by evaluating parameters like cost, number and types of used devices, and by comprehending the use of the overall network resources. The analysis of the collected results shows that there is no possibility to define a priori whether a grooming policy is better than another, nor that a network architecture excels: their optimality strongly relates to the network topology and traffic load. In the end, this work discusses how to exploit the different policies and routing constraints in the proposed algorithm for the multi-layer planning tool so as to reach the optimization goals associated with a specific design.