Type: Thesis (Masters)
Internet Traffic Engineering:
An Artificial Intelligence Approach.
Masters thesis, University of Porto.
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Due to the increasing popularity of the Internet, problems with current mechanisms for its management are becoming apparent. In particular, it is increasingly clear that
the Internet network does not provide sufficient support for the efficient control and management of traffic, i.e. for Traffic Engineering.
This dissertation addresses the problem of traffic engineering on the Internet from an Artificial Intelligence perspective. It argues that Internet traffic engineering should be automated instead of being performed reactively as response to undesirable network states. It presents and evaluates mechanisms for Internet traffic engineering based on Artificial Intelligence methods.
This dissertation also discusses a suitable architecture for the application of the proposed mechanisms. It argues that the proposed mechanisms are able to support a wide range of services useful for both users and operators.
Finally, in a network of the size of the Internet consideration must also be given to the deployment of the
proposed solutions. Consequently, arguments for and against the deployment of these mechanisms are presented and the conclusion drawn that there are a number of feasible
paths toward deployment.
The work presented argues the following: firstly, it is possible to implement mechanisms within the Internet framework that extend current protocols and algorithms and enable traffic engineering to be carried out by operators; secondly, that applying these mechanisms reduces human intervention together with the management problems faced by perators and at the same time the efficiency with which the etwork can be run is improved; thirdly, that these mprovements can correspond to increased network performance has viewed by the user; and finally, that not only the resulting deployment but also the deployment process itself are feasible.
Available Versions of this Item
- Internet Traffic Engineering:
An Artificial Intelligence Approach (deposited 22 February 2005) [Currently Displayed]
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