Um sistema de engenharia de tráfego autogerenciável para redes IP

• Ano de defesa: 2013
• Autor(a) principal: Pedro Dias de Oliveira Carvalho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Engenharia Elétrica; Interconexão de redes (Telecomunicações); Engenharia elétrica
• Link de acesso: http://hdl.handle.net/1843/BUOS-9LNGCG

The offer of a service bundle, which includes phone, television and Internet, is still delivered most often through separate telecommunications networks even though it is consolidated among telecom operators. The convergence of these services into a single network would save on costs of implementation, expansion and maintenance. The growing diversity of multimedia devices such as netbooks, smartphones, tablets, smartTVs and augmented reality glasses, among others compatible with the IP networks is an indication that this is the ideal network for convergence. However, different services in addition to the diversity of multimedia devices generate a dynamic, complex and unpredictable traffic profile, for which the current network management scheme becomes slow and inefficient. The proposal of this work is a self-managed traffic engineering system in which the network operation and maintenance are performed efficiently and without human intervention. The ns-2 simulator was used for the performance evaluation of the proposed system. Different scenarios were configured in this environment with Variable Bit Rate (VBR) flows from real videos and Constant Bit Rate (CBR) flows. The results show that when the available resources in the network are greater than the services demand, the self-managing system is able to optimize the resources allocation in order to meet the demand with the required quality, distributing the network load when possible. However, when demand is greater than the resources that the network can provide, the system seeks to maximize demand allocation without sacrificing the broadcast quality. The behavior of the system in the occurrence of a link failure was also assessed and showed that the system is capable of reacting without human interference, adapting to the new network state to continue delivering the affected services.