Alocação de Recursos em Redes Ópticas Elásticas com Multiplexação por Divisão Espacial Considerando Limitações da Camada Física

• Autor(a) principal: LACERDA JÚNIOR, Jurandir Cavalcante
• Data de Publicação: 2024
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFMA
• Texto Completo: https://tedebc.ufma.br/jspui/handle/tede/tede/5264
• topic: redes ópticas elásticas;; multiplexação por divisão espacial;; fibras multi-núcleos;; roteamento;; escolha de modulação;; alocação de núcleo e espectro;; limitações de camada física; elastic optical networks;; spatial division multiplexing;; multicore fiber;; routing;; modulation;; core and spectrum assignment;; physical layer impairments; Arquitetura de Sistemas de Computação

In recent years, the scientific community has indicated the space-division multiplexed elastic optical networks (SDM-EONs) to compose the infrastructure of transport networks and satisfy the growing demand for user traffic. In SDM-EONs based on uncoupled multi-core fiber (MCF), the optical fiber is composed of several cores, each with its own optical spectrum. A fundamental issue in the operation of an SDM-EON is the allocation of a new lightpath based on the arrival of requests for new connections. This question is related to the resource allocation problem, known as the routing, modulation, core, and spectrum assignment (RMCSA) problem. One of the challenges in solving the RMCSA problem is the physical layer impairments of the network. Physical layer impairments directly impact the quality of transmission of the network’s lightpaths. Among the diverse physical layer impairments, the inter-core crosstalk, the amplified spontaneous emission (ASE) noise, and the non-linear interference stand out. In this context, this thesis proposes algorithms to solve the resource allocation problem in SDM-EONs MCF-based, considering the network’s physical layer impairments. As contributions, five algorithms are proposed: i) the spectrum balancing algorithm (ABE); ii) the core balancing algorithm (ABN); iii) the machine learning-based algorithm for core selection (AMN); iv) the crosstalk-aware algorithm for core and spectrum allocation (ACiNE); and v) the inter-core crosstalk-aware and intra-core impairment- aware algorithm for modulation, core, and spectrum assignment (CIA-MCSA). The proposed algorithms are subjected to a performance evaluation process considering different modulation formats, operation in different network topologies, multi-core fibers with different coupling coefficients, dynamic traffic scenarios, and heterogeneous bit rate demands among customers. The numerical results show that, when compared to other proposals in the literature, the proposed algorithms have a lower circuit blocking probability and a lower bandwidth blocking probability.