Citas bibligráficas
Chávez, F., (2015). Redes neuronales artificiales para la optimización del cálculo de tiempo de ida y vuelta del protocolo de control de transmisión sobre Linux. [Tesis, Universidad Andina del Cusco]. https://hdl.handle.net/20.500.12557/18
Chávez, F., Redes neuronales artificiales para la optimización del cálculo de tiempo de ida y vuelta del protocolo de control de transmisión sobre Linux. [Tesis]. : Universidad Andina del Cusco; 2015. https://hdl.handle.net/20.500.12557/18
@misc{renati/1125646,
title = "Redes neuronales artificiales para la optimización del cálculo de tiempo de ida y vuelta del protocolo de control de transmisión sobre Linux.",
author = "Chávez Tejada, Fabrizzio",
publisher = "Universidad Andina del Cusco",
year = "2015"
}
Throughout the time, the traditional media such as radio, TV and printed press allowed for the exchange of information between different cultures and societies; however, the steady rise of new needs in different sectors such as education, business and social, demanded alternatives to expedite and improve the communication process. so for years we researched and designed new technological solutions, highlighting the forerunner ARPANET communications networks. This project was initially for military purposes, then used for academic purposes, and thereafter, with the advent of the Internet, global openness gave this technological model, giving emphasis to the age of information and knowledge. Internet communication is based on a stack of layered protocols segmented. Each layer has a specific purpose, ensuring the proper functioning of the hardware, proper management of software you want to use communications services and the establishment of rules for the exchange of information. The protocols are shaped by mathematical models and structures are constantly evolving and improved. In addition, artificial neural networks (ANN) are mathematical models that simulate the functioning of biological neural networks and are used in the field of artificial intelligence. Its properties allow building solutions for classification, pattern recognition and prediction by learning and adaptation mechanisms. This research analyzed the round trip time (RTT) of segments transmitted in the communication transmission control protocol (TCP), it was designed and implemented based on neural network to replace the statistical model currently used in the source code model Linux kernel and performance between the current solution and the neural network was evaluated.
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