A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

Reconfigurable optical networks with dynamic physical impairments

Orientador: Helio WaldmanDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: As redes ópticas reconfiguráveis compõem o backbone de grande parte das redes de transporte em operação ao redor do mundo. No entanto, os desafios para ampliar a capacidade e eficiência destas redes ainda são enormes. Com objetivo de maximizar a carga útil de tráfego suportada nas redes ópticas WDM reconfiguráveis é de fundamental importância adotar eficientes algoritmos RWA. Os algoritmos RWA são responsáveis pela escolha adequada de recursos na rede para provisionar novas conexões de forma a maximizar a probabilidade de atendimento das futuras conexões. Nesta dissertação, o problema RWA será investigado sob diversas novas perspectivas através de um ambiente de simulação. Com a preocupação de retratar os reais problemas vivenciados pelas redes ópticas reconfiguráveis, os elementos de rede foram modelados de acordo com as tecnologias e arquiteturas atualmente empregadas no mercado. No caso dos elementos de comutação ROADM e amplificadores EDFA, serão adotadas modelagens ainda não exploradas na literatura relacionada ao problema RWA. Diversos estudos abordam o problema RWA levando em consideração as degradações de camada física na escolha dos recursos apropriados para o provisionamento de novas conexões. Esta abordagem é conhecida na literatura como RWA-IA. Neste trabalho será adotada uma abordagem mais realista, considerando não apenas as condições de camada física para o provisionamento de novas conexões, mas também o impacto na camada física causado pelo estabelecimento de novas conexões nas demais já ativas na rede. Ainda neste trabalho serão propostos dois novos algoritmos de alocação de comprimento de onda sensíveis às degradações dinâmicas da camada física. Um extenso estudo com a avaliação de desempenho destes algoritmos será realizado, contemplando também um estudo comparativo com outros algoritmos encontrados na literatura e utilizados com frequência no mercado. Os algoritmos propostos demonstraram excelente desempenho, conseguindo inclusive superar o desempenho dos demais algoritmos avaliados em termos de probabilidade de bloqueioAbstract: Reconfigurable optical networks has been adopted as the backbone solution by most of transport networks around the world. However, in order to expand the capacity and efficiency of these networks, there are still many challenges to overcome. In order to improve the reconfigurable optical network capacity is very important to work with efficient RWA algorithms capable to find appropriate network resources for new lightpaths and, at the same, to minimize the blocking probability of future demands. In this dissertation, the RWA problem will be investigated under several new perspectives through a simulation environment. Committed to retract real problems experienced by reconfigurable optical networks, network elements were design according to the technologies and architectures currently employed in the industry. The ROADM switching elements and EDFA amplifiers were design in an unprecedented way in the RWA literature. Several studies addressing the RWA problem have already incorporated the physical layer impairments in order to find the appropriate resources for establishing new lightpaths. This approach has become known in the literature as Impairment Aware RWA (IA-RWA). In this dissertation, we adopted a more realistic approach to the RWA-IA problem, also considering the impact on the physical layer caused by the establishment of new connections in the others already established in the network. Moreover, in this work we will propose two new wavelength assignment algorithms aware to the physical layer dynamic impairments. An extensive performance evaluation study about these algorithms will be performed, also contemplating a comparative study with other algorithms from the literature and widely used in the industry. The proposed new algorithms have shown excellent performance, outperforming other algorithms evaluated in terms of blocking probabilityMestradoTelecomunicações e TelemáticaMestre em Engenharia Elétric