The main characteristic of various emerging communication network paradigms in the dimensioning, control and deployment of future networks is the fact that they are human-centric, entailing closelyknit interactions between telematics and human activities. Considering the effect of user behavior, whose dynamics are difficult to model, new uncertainties are introduced in these systems, bringing about network resource management challenges. Within this context, this study seeks to review different decision-making computational methods in conditions of uncertainty for Internet of Things scenarios such as smart spaces, and industry 4.0, through a systematic literature review. According to our research results, a new paradigm for computationally capturing and modeling human behavior context must be developed with the purpose of improving resource management.

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Parte C_^ Caracterización del tráfico 56 Cl. Tipos de tráfico 56 C2. Nivelización del tráfico 59 C3. Modelos de tráfico para evaluación de dispositivos ATM 61 Conclusiones Parte C. 67 Parte D^ Fuentes de tráfico utilizadas en esta tesis. 68 DI. Modelo de dos estados 68 D2. Tráfico real de video 69 D2.1 Clasificación del tráfico 70 D2.2 Caracterización del tráfico 72 Conclusiones Parte D. 73 Parte E_._ Funciones de control de congestión. 74 El. Necesidad de su existencia 74 E2. Modelo de Sistema de Gestión de Red 76 E2.1 Gestión global de red 78 E2.2 Control de llamadas 80 E2.3 Control de congestión 81 E3. Prioridades. 81 E4. Control de admisiones 83 E4.1 Valor de pico 85 E4.2 Aproximación por convolución 85