Performance modeling and knowledge processing in high-speed interconnected intelligent educational networks.
Item
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Title
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Performance modeling and knowledge processing in high-speed interconnected intelligent educational networks.
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Identifier
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AAI3283160
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identifier
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3283160
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Creator
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Pinto, Marcos Silva.
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Contributor
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Adviser: Syed V. Ahamed
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Date
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2007
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Language
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English
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Publisher
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City University of New York.
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Subject
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Computer Science
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Abstract
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The objective of all network designers and administrators is to have a network that provides flawlessly the services that users and businesses need. This research will focus on network traffic and customer services in the academic world environment that optimize knowledge processing. The approach is to suggest that once the network traffic behavior is controlled and services can be customized intelligently then the first steps to bring the benefits of the knowledge superhighway to everyone in the world can be taken. First we will analyze traffic characteristics of campus networks in order to develop insight into their operation and performance by developing tractable models and approximations. Then, in the second part of the thesis, we will keep the same optimized campus network structure but now with the addition of intelligent components turning the network into an intelligent educational network which provides knowledge processing. We propose a methodology for understanding network traffic behavior through the combination of quality of service, degradation policies, and a queue scheme. We also suggest a new approach in routing intelligently network packets. The idea is to divide the application layer into layers that deals with the following: the forwarding packet process, the quality of service integrated into the packet, and finally the type of application the packet belongs to.;The overall purpose of this research is twosome: (i) to optimize high-performance educational networks, implemented as national and global campus networks, by simulating their operations and analyzing their performance based on certain traffic parameters and network characteristics, and (ii) to suggest a general fine-tuned architecture of an intelligent educational systems running on these optimized networks that ultimately acts as a 'negotiator' between a knowledge seeker and knowledge repositories---a matchmaker systems that selects the right set of knowledge data banks (output) after interpreting correctly incoming information request (input).
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Type
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dissertation
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Source
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PQT Legacy CUNY.xlsx
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degree
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Ph.D.
