A study on ENUM delegation model: An Autonomic Simulation Platform for Studying and Optimizing Addressing Issues in NGN - Image 1

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LAP Lambert Academic Publishing A study on ENUM delegation model: An Autonomic Simulation Platform for Studying and Optimizing Addressing Issues in NGN

Name: A study on ENUM delegation model: An Autonomic Simulation Platform for Studying and Optimizing Addressing Issues in NGN
Brand: LAP Lambert Academic Publishing
Price: 55.0 GBP
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Network Topics

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Description

We focus on studying the addressing issues in Next Generation Networks; between traditional telephony and the Internet world. Addressing users and services uniquely across network boundaries without exploding the address space is one of the key challenges of NGN. ENUM uses a single address identifier for communicating with multiple communication services across different types of networks. Difficulty in studying real ENUM implementation is the motivation to implement a simulation platform. We designed a new way to measure and model the local performance of DNS servers of the French ENUM model. We also modeled and measured the IP links connecting the DNS namely; Resolver, Cache and Authoritative servers. Finally we created a simulation model which enables us to simulate ENUM traffic. This platform needs to be autonomic, so that it can adapt itself depending on the input configuration. In this thesis work we explain how the simulation model is designed to be an autonomic simulation platform. Different experiments are run using the simulation model, and we present how the solutions obtained from the simulation can be used as recommendations back in real implementation

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3659150088
Category: Books > Subjects > Computing & Internet > Networking & Security > Network Topics
Domain: Amazon UK
Release Date: 13 June 2012
Listed Since: 19 June 2012

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LAP Lambert Academic Publishing A study on ENUM delegation model: An Autonomic Simulation Platform for Studying and Optimizing Addressing Issues in NGN

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