Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Performance analysis of predictive trigger algorithm for mobile wimax networks(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2009-07-01) Urbina Pineda, Julia; URBINA PINEDA, JULIA; 213230; Muñoz Rodríguez, David; tolmquevedo; Tecnológico de Monterrey, Campus MonterreyA major consideration for mobile WiMAX is Seamless Handover. Cellular-based standards have the advantage of many years experience in handover for voice calls, while for broadband mobility in itself is no mean feat, and handover is still a challenge. IEEE 802.16e (Mobile WiMAX) is a wireless metropolitan area network standard with high transmission speed and great coverage. This work will address the handover process; an important issue of Mobile WiMAX system. This thesis considers the importance to have the correct handover initiation process. By using a predictive algorithm, in hands of the threshold that triggers the handover process based on RSSI. We study in this thesis the intracellular and intercellular handover process in Mobile WiMAX system. We focus in particular on the impact of use a predictive trigger algorithm in order to ensure a success handover process. We demonstrate that using a predictive algorithm offers a significantly advantage over the traditional algorithm of handover process.
- URN Modeling for Heavy-Tailed Phenomena(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2003-12-01) Rodríguez Morales, Oscar; Muñoz Rodríguez, David; tolmquevedo; Tecnológico de Monterrey, Campus MonterreyDuring the last decade, it was clear that the use of Poisson processes for modeling network traffic underestimated certain important performance measures such as blocking or queueing delay, among others. Researches around the world agree with the presence of heavy-tail behavior in almost all the data traffic’s metrics, such as connection arrivals, file sizes, central processing unit (CPU) time demands of UNIX processes, etc. As a result, during the next few years, heavy-tailed distributions will play a principal role in the modelling and developing of telecommunications systems. Due to the nature of data traffic, researches demand a discrete heavy-tail distribution, perfectly well described, that enables them to reflect the impact of the two states present in all digital systems (on/off, successful/failed, connect/disconnected, enabled/disabled) in the tail decay. At the present time, there is no distribution with this high degree of flexibility. This thesis completes the description of the discrete heavy-tail distribution introduced in [24] by getting their moments and variance derived from a rigorous generating functions analysis. It validates the model’s heavy-tail nature through mean excess functions and some related plots such as the Quantile-Quantile or Probability-Probability plot. Also, the model’s stability and their match with the Pareto distribution are investigated. This work concludes with a discussion about the initial conditions influence in the model’s tail decay.