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Enhanced convolution approach for CAC in ATM networks, an analytical study and implementationMarzo i Lázaro, Josep Lluís 07 February 1997 (has links)
The characteristics of service independence and flexibility of ATM networks make the control problems of such networks very critical. One of the main challenges in ATM networks is to design traffic control mechanisms that enable both economically efficient use of the network resources and desired quality of service to higher layer applications. Window flow control mechanisms of traditional packet switched networks are not well suited to real time services, at the speeds envisaged for the future networks. In this work, the utilisation of the Probability of Congestion (PC) as a bandwidth decision parameter is presented. The validity of PC utilisation is compared with QOS parameters in buffer-less environments when only the cell loss ratio (CLR) parameter is relevant. The convolution algorithm is a good solution for CAC in ATM networks with small buffers. If the source characteristics are known, the actual CLR can be very well estimated. Furthermore, this estimation is always conservative, allowing the retention of the network performance guarantees. Several experiments have been carried out and investigated to explain the deviation between the proposed method and the simulation. Time parameters for burst length and different buffer sizes have been considered. Experiments to confine the limits of the burst length with respect to the buffer size conclude that a minimum buffer size is necessary to achieve adequate cell contention. Note that propagation delay is a no dismiss limit for long distance and interactive communications, then small buffer must be used in order to minimise delay. Under previous premises, the convolution approach is the most accurate method used in bandwidth allocation. This method gives enough accuracy in both homogeneous and heterogeneous networks. But, the convolution approach has a considerable computation cost and a high number of accumulated calculations. To overcome this drawbacks, a new method of evaluation is analysed: the Enhanced Convolution Approach (ECA). In ECA, traffic is grouped in classes of identical parameters. By using the multinomial distribution function instead of the formula-based convolution, a partial state corresponding to each class of traffic is obtained. Finally, the global state probabilities are evaluated by multi-convolution of the partial results. This method avoids accumulated calculations and saves storage requirements, specially in complex scenarios. Sorting is the dominant factor for the formula-based convolution, whereas cost evaluation is the dominant factor for the enhanced convolution. A set of cut-off mechanisms are introduced to reduce the complexity of the ECA evaluation. The ECA also computes the CLR for each j-class of traffic (CLRj), an expression for the CLRj evaluation is also presented. We can conclude that by combining the ECA method with cut-off mechanisms, utilisation of ECA in real-time CAC environments as a single level scheme is always possible.
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Mejora en la estimación de presupuestos de edificios multifamiliares mediante el método de Monte Carlo aplicado a riesgos con diferente comportamiento en la fase de planificación de proyecto. / Improvement in the estimation of multifamily building budgets through the Monte Carlo method applied to risks with different behavior in the project planning phaseGarcía Martín, Sergio 11 November 2020 (has links)
Actualmente, los riesgos de diferente comportamiento (variabilidad y vinculados a eventos) pueden afectar a las edificaciones multifamiliares, generando importantes sobrecostos y desviaciones presupuestales.
Esta tesis se enfoca en la elaboración de una metodología pauteada que sirva como herramienta aplicativa para cualquier proyecto de edificio multifamiliar, independientemente de su ubicación. Se ha diferenciado el análisis de los riesgos bajo las dos tipologías mencionadas por el PMBOK en su sexta edición (variabilidad y vinculados a eventos), como una tendencia novedosa.
En la investigación primeramente se desarrolla una encuesta de juicio experto para identificar los riesgos más frecuentes en la muestra de estudio (distrito de Miraflores, ciudad de Lima). Seguidamente, se realiza una entrevista a los profesionales responsables de los tres proyectos que se toman como caso de estudio. En las mismas se recaban todos los datos necesarios para realizar a continuación el análisis cualitativo y el análisis cuantitativo de los diferentes riesgos investigados. Para el análisis cuantitativo se utiliza el método de Monte Carlo, a través del software @RISK. En cada proyecto se obtienen los valores de los riesgos en forma de contingencia, relacionados con el Costo Directo del presupuesto.
Finalmente, a través de las convoluciones, se determinan los valores de la contingencia de los riesgos generales, o combinación simultánea de los riesgos de variabilidad y vinculados a eventos.
Se puede concluir que esta metodología es muy beneficiosa al implementarse en etapas tempranas o de planificación, pues permite cuantificar los riesgos, en aras de mitigarlos y controlarlos durante la ejecución del proyecto. / Currently, the risks of different behavior (variability and linked to events) can affect multifamily buildings, generating significant cost overruns and budget deviations.
This thesis focuses on the elaboration of a methodology that serves as an application tool for any multi-family building project, regardless of its location. The risk analysis has been differentiated under the two typologies mentioned by the PMBOK in its sixth edition (variability and linked to events), as a novel trend.
The investigation first develops an expert judgment survey to identify the most frequent risks in the study sample (Miraflores district, Lima city). Next, an interview is conducted with the professionals responsible for the three projects that are taken as a case study. They collect all the necessary data to carry out the qualitative analysis and the quantitative analysis of the different risks investigated. The Monte Carlo method is used for quantitative analysis, through the @RISK software. In each project the values of the risks are obtained in the form of contingency, related to the Direct Cost of the budget.
Finally, through the convolutions, the values of the contingency of the general risks, or simultaneous combination of the risks of variability and linked to events are determined.
It can be concluded that this methodology is very beneficial when implemented in early stages or planning, since it allows quantifying the risks, in order to mitigate and control them during the execution of the project. / Tesis
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