Title page for ETD etd-11197-12405

Type of Document

Dissertation

Author

Brande, Julia K. Jr.

Author's Email Address

Julia_Earp@ncsu.edu

URN

etd-11197-12405

Title

Computer Network Routing with a Fuzzy Neural Network

Degree

PhD

Department

Management Science and Information Technology

Advisory Committee

Advisor Name	Title
Clayton, Edward R.
Moore, Laurence J.
Rees, Loren Paul
Sumichrast, Robert T.
Rakes, Terry R.	Committee Chair

Keywords

Network Routing
Fuzzy Reasoning
Neural Networks
Wide Area Networks

Date of Defense

1997-11-07

Availability

unrestricted

Abstract

The growing usage of computer networks is requiring improvements in network technologies
and management techniques so users will receive high quality service. As more individuals
transmit data through a computer network, the quality of service received by the users begins
to degrade. A major aspect of computer networks that is vital to quality of service is data
routing. A more effective method for routing data through a computer network can assist with
the new problems being encountered with today's growing networks.
Effective routing algorithms use various techniques to determine the most appropriate route
for transmitting data. Determining the best route through a wide area network (WAN),
requires the routing algorithm to obtain information concerning all of the nodes, links, and
devices present on the network. The most relevant routing information involves various
measures that are often obtained in an imprecise or inaccurate manner, thus suggesting that
fuzzy reasoning is a natural method to employ in an improved routing scheme. The neural
network is deemed as a suitable accompaniment because it maintains the ability to learn in
dynamic situations. Once the neural network is initially designed, any alterations in the
computer routing environment can easily be learned by this adaptive artificial intelligence
method. The capability to learn and adapt is essential in today's rapidly growing and
changing computer networks. These techniques, fuzzy reasoning and neural networks, when
combined together provide a very effective routing algorithm for computer networks.
Computer simulation is employed to prove the new fuzzy routing algorithm outperforms the
Shortest Path First (SPF) algorithm in most computer network situations. The benefits
increase as the computer network migrates from a stable network to a more variable one. The
advantages of applying this fuzzy routing algorithm are apparent when considering the
dynamic nature of modern computer networks.

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